Battery diagnostic device and method of operating the same

Abstract

A battery diagnostic apparatus according to embodiments disclosed in this document can include: an acquisition unit configured to acquire open circuit voltage (OCV) data of a plurality of battery cells; a calculation unit configured to calculate, for each of the plurality of battery cells, an OCV difference value between a first OCV value and a second OCV value based on the OCV data, wherein the first OCV value corresponds to a first charge / discharge cycle and the second OCV value corresponds to a second charge / discharge cycle after the first charge / discharge cycle; a normalization unit configured to acquire normalized OCV difference values by normalizing the OCV difference values of the plurality of battery cells; an identification unit configured to identify a suspected abnormal battery cell among the plurality of battery cells based on the normalized OCV difference values; and a diagnosis unit configured to diagnose an abnormality of the suspected abnormal battery cell based on an OCV deviation value between the second OCV value of the identified suspected abnormal battery cell and a representative value of the second OCV values of the plurality of battery cells.

Description

Technical Field

[0001] Cross-reference to related applications

[0002] This application claims the benefit of priority to Korean Patent Application No. 10-2024-0002060, filed on January 5, 2024, which is incorporated herein by reference in its entirety. Technical Field

[0003] The embodiments disclosed in this document relate to battery diagnostic devices and their operating methods. Background Technology

[0004] Recently, research and development of rechargeable batteries have been actively pursued. Rechargeable batteries are batteries that can be charged and discharged, and include conventional Ni / Cd batteries, Ni / MH batteries, and more recently, lithium-ion batteries. Among rechargeable batteries, lithium-ion batteries have the advantage of a much higher energy density than conventional Ni / Cd and Ni / MH batteries. Furthermore, lithium-ion batteries can be manufactured in a small and lightweight manner, making them suitable for use as power sources in mobile devices. Recently, the applications of lithium-ion batteries have expanded to include power sources for electric vehicles, and they are attracting attention as a next-generation energy storage medium.

[0005] Additionally, secondary batteries can typically be used as battery packs comprising battery modules, in which multiple battery cells are connected in series and / or parallel within each module. Furthermore, secondary batteries can be used as battery racks comprising multiple battery modules and as frame structures housing these battery modules.

[0006] These battery cells, modules, packs, or racks can be used in a variety of devices. For example, they can be used not only in mobile devices such as mobile phones, laptops, smartphones, and tablets, but also in electric vehicles (EVs, HEVs, PHEVs) and energy storage devices (ESS).

[0007] The state and operation of these batteries can be managed and controlled by a battery management system (BMS). The battery management system can be included in a device along with the batteries.

[0008] Furthermore, a battery management system can manage and control the battery while remaining separate 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 the vehicle, etc., and use the collected data to manage and control the battery. Summary of the Invention

[0009] Technical issues

[0010] On the other hand, when defects exist in the battery, the likelihood of damage to devices including the battery (e.g., EVs, ESS) may increase. Therefore, a method is needed to detect abnormal battery conditions and reduce the likelihood of damage to devices including the battery.

[0011] The embodiments disclosed in this document provide a battery diagnostic device and its operating method that can use the charge / discharge cycle open-circuit voltage (OCV) difference to diagnose battery abnormalities.

[0012] The technical problems of the embodiments disclosed in this document are not limited to the above-described technical problems, and other technical problems not mentioned can be clearly understood by those skilled in the art from the following description.

[0013] Technical solution

[0014] A battery diagnostic apparatus according to one embodiment disclosed in this document may include: an acquisition unit that acquires open-circuit voltage (OCV) data of a plurality of battery cells; a calculation unit that calculates, based on the OCV data, an OCV difference between a first OCV value corresponding to a first charge / discharge cycle and a second OCV value corresponding to a second charge / discharge cycle following the first charge / discharge cycle for each of the plurality of battery cells; a normalization unit that acquires a normalized OCV difference by normalizing the OCV differences of the plurality of battery cells; an identification unit that identifies suspected abnormal battery cells among the plurality of battery cells based on the normalized OCV differences; and a diagnostic unit that diagnoses the abnormality of the suspected abnormal battery cells based on an OCV deviation value between the second OCV value of the identified suspected abnormal battery cell and a representative value of the second OCV values ​​of the plurality of battery cells.

[0015] In a battery diagnostic device according to one embodiment disclosed in this document, a normalization unit can normalize the OCV differences of multiple battery cells based on Equation 1 below to obtain normalized OCV differences.

[0016] [Formula 1]

[0017] (In Equation 1, dOCV) i dOCV is the OCV difference of the i-th battery cell among multiple battery cells. min It is the minimum value among the OCV differences of multiple battery cells, and dOCV max It is the maximum value among the OCV differences of multiple battery cells.

[0018] In a battery diagnostic device according to one embodiment disclosed in this document, the identification unit can identify suspected abnormal battery cells among a plurality of battery cells based on the deviation between normalized OCV differences.

[0019] In a battery diagnostic device according to one embodiment disclosed in this document, when the deviation between the maximum value and the second largest value in the normalized OCV difference is greater than or equal to a first threshold, the identification unit can identify the battery cell with the maximum value as a suspected abnormal battery cell.

[0020] In a battery diagnostic device according to one embodiment disclosed in this document, when the deviation between the minimum value and the second minimum value in the normalized OCV difference is greater than or equal to a second threshold, the identification unit can identify the battery cell with the minimum value as a suspected abnormal battery cell.

[0021] In a battery diagnostic device according to one embodiment disclosed in this document, when the OCV deviation value of a suspected abnormal battery cell is greater than or equal to a third threshold, the diagnostic unit can diagnose the suspected abnormal battery cell as an abnormal battery cell.

[0022] In a battery diagnostic device according to one embodiment disclosed in this document, the first OCV value may be an OCV value corresponding to a charging cycle included in a first charging / discharging cycle, and the second OCV value may be an OCV value corresponding to a charging cycle included in a second charging / discharging cycle.

[0023] In a battery diagnostic device according to one embodiment disclosed in this document, the first OCV value may be an OCV value corresponding to a discharge cycle included in a first charge / discharge cycle, and the second OCV value may be an OCV value corresponding to a discharge cycle included in a second charge / discharge cycle.

[0024] An operation method of a battery diagnostic device according to one embodiment disclosed in this document may include: acquiring open-circuit voltage (OCV) data of a plurality of battery cells; calculating, based on the OCV data, an OCV difference between a first OCV value corresponding to a first charge / discharge cycle and a second OCV value corresponding to a second charge / discharge cycle following the first charge / discharge cycle for each of the plurality of battery cells; acquiring a normalized OCV difference by normalizing the OCV differences of the plurality of battery cells; identifying a suspected abnormal battery cell among the plurality of battery cells based on the normalized OCV difference; and diagnosing an abnormality of the suspected abnormal battery cell based on an OCV deviation value between the second OCV value of the identified suspected abnormal battery cell and a representative value of the second OCV values ​​of the plurality of battery cells.

[0025] In the operation method of a battery diagnostic device according to one embodiment disclosed in this document, the operation of obtaining the normalized OCV difference may include obtaining the normalized OCV difference by normalizing the OCV difference of multiple battery cells based on Equation 1 above.

[0026] In the operation method of a battery diagnostic device according to one embodiment disclosed in this document, the operation of identifying suspected abnormal battery cells may include identifying suspected abnormal battery cells among a plurality of battery cells based on the deviation between normalized OCV differences.

[0027] In the operation method of a battery diagnostic device according to one embodiment disclosed in this document, the operation of identifying suspected abnormal battery cells may include identifying the battery cell with the maximum value as a suspected abnormal battery cell when the deviation between the maximum value and the second maximum value in the normalized OCV difference is greater than or equal to a first threshold.

[0028] In the operation method of a battery diagnostic device according to one embodiment disclosed in this document, the operation of identifying suspected abnormal battery cells may include identifying a battery cell with the minimum value as a suspected abnormal battery cell when the deviation between the minimum value and the second minimum value in the normalized OCV difference is greater than or equal to a second threshold.

[0029] In the operation method of a battery diagnostic device according to one embodiment disclosed in this document, the operation of diagnosing the abnormality of a suspected abnormal battery cell may include diagnosing the suspected abnormal battery cell as an abnormal battery cell when the OCV deviation value of the suspected abnormal battery cell is greater than or equal to a third threshold.

[0030] In the operation method of a battery diagnostic device according to one embodiment disclosed in this document, the first OCV value may be an OCV value corresponding to a charging cycle included in a first charging / discharging cycle, and the second OCV value may be an OCV value corresponding to a charging cycle included in a second charging / discharging cycle.

[0031] Beneficial effects

[0032] According to the implementation methods disclosed in this document, minor abnormal behaviors of battery voltage can be accurately diagnosed by normalizing the OCV difference.

[0033] In addition, various effects that can be directly or indirectly identified through this document can be provided. Attached Figure Description

[0034] Figure 1 This is a block diagram of a battery diagnostic device according to one embodiment.

[0035] Figure 2a and Figure 2b This is a graph illustrating the OCV difference calculated by a battery diagnostic device for each of a plurality of battery cells according to one embodiment.

[0036] Figure 3 This is a graph illustrating a normalized OCV difference obtained by normalizing the OCV difference using a battery diagnostic device, according to one embodiment.

[0037] Figure 4 This is a flowchart illustrating the operation of a battery diagnostic device according to one embodiment. Detailed Implementation

[0038] In the following description, embodiments described in this document are illustrated with reference to the accompanying drawings. However, this is not intended to limit the disclosure of this document to the specific embodiments, but should be understood to include various modifications, equivalents, and / or substitutions of the embodiments described in this document.

[0039] The various embodiments and terminology used in this document are not intended to limit the technical features described herein to specific embodiments, but should be understood to include various modifications, equivalents, or substitutions of the embodiments. Similar reference numerals may be used for similar or related components in conjunction with the description of the accompanying drawings. Unless the context clearly indicates otherwise, the singular form of the noun corresponding to an item may include one or more of the items mentioned.

[0040] In this document, each of 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 include any one of the items listed together in that phrase or all possible combinations thereof. Unless otherwise specifically stated, terms such as “first,” “second,” “firstly,” “secondarily,” “A,” “B,” “(a),” or “(b)” may be used only to distinguish one component from another and do not limit the components in any other way (e.g., in terms of importance or order).

[0041] In this document, when a component (e.g., a first component) is referred to as “connected,” “joined,” or “attached” to another component (e.g., a second component) with or without the terms “functionally” or “communically”, it means that the component can be connected to the other component directly (e.g., via a wired connection), wirelessly, or via a third component.

[0042] According to various embodiments, each of the above-described components (e.g., modules or programs) may include a single entity or multiple entities, and some of the multiple entities may be separated and placed in other components. According to various embodiments, one or more of the above-described 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 the functions performed by the corresponding components among the multiple components prior to integration. According to various embodiments, operations performed by modules, programs, or other components may be performed sequentially, in parallel, repeatedly, or heuristically, or may be performed in a different order, by omitting one or more operations, or by adding one or more other operations.

[0043] Figure 1 This is a block diagram of a battery diagnostic device according to one embodiment.

[0044] The battery diagnostic device 101 described below can be implemented as a battery management system (BMS) within an electronic device 102, and can also be implemented as various external devices such as a server, cloud, charger, or charger / discharger.

[0045] Reference Figure 1 The battery diagnostic device 101 can be connected to the electronic device 102 and the user terminal 104 via wired and / or wireless means.

[0046] According to one embodiment, the connection 103 between the battery diagnostic device 101 and the electronic device 102 can be a communication connection via a wired network and / or a wireless network. In one embodiment, the wired network can be based on local area network (LAN) communication or power line communication. In one embodiment, the wireless network can be based on a short-range communication network (e.g., Bluetooth, Wi-Fi, or Infrared Data Association (IrDA)) or a long-range communication network (cellular network, 4G network, 5G network).

[0047] According to another embodiment, the connection 103 between the battery diagnostic device 101 and the electronic device 102 may be a connection via an inter-device communication method (e.g., bus, general purpose input and output (GPIO), serial peripheral interface (SPI), or mobile industrial processor interface (MIPI)).

[0048] According to one embodiment, the electronic device 102 may be a mobile device (e.g., a mobile phone, a laptop, a smartphone, a smart tablet), an electric vehicle (e.g., an electric vehicle (EV), a hybrid electric vehicle (HEV), a plug-in hybrid electric vehicle (PHEV)), a fuel cell electric vehicle (FCEV), an energy storage system (ESS), or a battery swapping system (BSS).

[0049] According to one embodiment, the electronic device 102 may include a plurality of battery cells 151, 153, and 155. According to one embodiment, the plurality of battery cells 151, 153, and 155 may be included in a battery module or a battery pack.

[0050] According to one embodiment, the connection 105 between the battery diagnostic device 101 and the user terminal 104 can be a communication connection via a wired network and / or a wireless network.

[0051] According to one embodiment, the user terminal 104 may be a mobile device (e.g., a mobile phone, laptop computer, smartphone, and tablet computer) or a personal computer (PC). According to one embodiment, the battery diagnostic device 101 may provide the user terminal 104 with information related to the diagnostic results of battery cells 151, 153, or 155.

[0052] 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 one embodiment, Figure 1 The battery diagnostic device 101 shown may also include, in addition to Figure 1 At least one component other than the components shown (e.g., display, input device, or output device), or which may be omitted. Figure 1 At least one of the components shown (e.g., sensor 120). 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 use the communication circuit 110 to acquire status information of multiple battery cells 151, 153, and 155. In this case, sensor 120 may not be included in the battery diagnostic device 101.

[0053] 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 can send data to and receive data from the electronic device 102 and / or the user terminal 104 through the established communication channel.

[0054] According to one embodiment, sensor 120 can measure information (e.g., voltage, current, temperature, etc.) related to the state of multiple battery cells 151, 153, and 155 of electronic device 102. For example, when battery diagnostic device 101 is implemented as a BMS within electronic device, battery diagnostic device 101 can use sensor 120 to directly measure the state values ​​of multiple battery cells 151, 153, and 155.

[0055] According to one embodiment, the communication circuit 110 and / or sensor 120 can acquire time-series data related to the state of a plurality of battery cells 151, 153, and 155. In one embodiment, the time-series data related to the state of the plurality of battery cells 151, 153, and 155 may be data representing the voltage, current, resistance, state of charge (SOC), state of health (SOH), and / or temperature of the plurality of battery cells 151, 153, and 155 over time.

[0056] According to one embodiment, memory 130 may include volatile memory and / or non-volatile memory.

[0057] According to one embodiment, memory 130 may store data used by at least one component of battery diagnostic device 101 (e.g., processor 140). For example, the data may include software (or associated instructions), input data, or output data. In one embodiment, instructions, when executed by processor 140, may cause battery diagnostic device 101 to perform operations defined by the instructions.

[0058] According to one embodiment, the memory 130 may include one or more software (e.g., acquisition unit 131, calculation unit 132, normalization unit 133, identification unit 134, and diagnostic unit 135).

[0059] According to one embodiment, 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.

[0060] According to one embodiment, the processor 140 can execute software (e.g., acquisition unit 131, calculation unit 132, normalization unit 133, identification unit 134, and diagnostic unit 135) stored in the memory 130 to control at least one other component (e.g., hardware component or software component) of the battery diagnostic device 101 connected to the processor 140, and can perform various data processing or calculations.

[0061] In the following text, reference will be made to Figure 2a , Figure 2b and Figure 3The method described is as follows: the battery diagnostic device 101 diagnoses anomalies of multiple battery cells 151, 153 and 155 by means of an acquisition unit 131, a calculation unit 132, a normalization unit 133, an identification unit 134 and a diagnostic unit 135.

[0062] Figure 2a and Figure 2b This is a graph illustrating the OCV difference calculated by a battery diagnostic device for each of a plurality of battery cells according to one embodiment. Figure 3 This is a graph illustrating the normalized OCV difference obtained by normalizing the OCV difference using a battery diagnostic device, according to an embodiment.

[0063] According to one embodiment, the acquisition unit 131 can acquire open-circuit voltage (OCV) data of a plurality of battery cells 151, 153, and 155. For example, the acquisition unit 131 can measure the voltage, current, and / or temperature of the plurality of battery cells 151, 153, and 155 and generate OCV data based on the measured information. In this case, the acquisition unit 131 can use sensor 120 to measure the voltage, current, and / or temperature of the plurality of battery cells 151, 153, and 155. As another example, the acquisition unit 131 can use communication circuit 110 to receive OCV data of the plurality of battery cells 151, 153, and 155 generated by electronic device 102.

[0064] According to one embodiment, the calculation unit 132 can calculate an OCV difference for each of the plurality of battery cells 151, 153, and 155 based on OCV data. The OCV difference can be the difference between two corresponding OCV values ​​in each of two charge / discharge cycles within a plurality of charge / discharge cycles included in the time period of the OCV data. Here, a charge / discharge cycle can include a charging cycle and a discharging cycle.

[0065] According to one embodiment, the OCV difference can be the difference between a first OCV value corresponding to a first charge / discharge cycle and a second OCV value corresponding to a second charge / discharge cycle in a plurality of charge / discharge cycles. In this case, the second charge / discharge cycle can be a cycle adjacent to the first charge / discharge cycle after the first charge / discharge cycle. Alternatively, the OCV difference can be a value obtained by subtracting the first OCV value from the second OCV value.

[0066] In the following text, the current charge / discharge cycle to be diagnosed may be referred to as the second charge / discharge cycle, and the immediately preceding charge / discharge cycle may be referred to as the first charge / discharge cycle. Furthermore, the OCV values ​​of battery cells 151, 153, and / or 155 corresponding to the first charge / discharge cycle may be referred to as the first OCV value, and the OCV values ​​of battery cells 151, 153, and / or 155 corresponding to the second charge / discharge cycle may be referred to as the second OCV value.

[0067] According to one embodiment, the calculation unit 132 can calculate the OCV difference based on a type of charging cycle or discharging cycle included in the charging / discharging cycle.

[0068] For example, the calculation unit 132 can calculate the OCV difference between a first OCV value corresponding to a first charging cycle and a second OCV value corresponding to a second charging cycle following the first charging cycle, within a time period of OCV data. In this case, the OCV value corresponding to each charging cycle can be selected as the OCV value at a time point after a specified time (e.g., 2 hours) after the end of each charging cycle. For example, the calculation unit 132 can calculate the OCV difference as the difference between the first OCV value at a time point after a specified time after the end of the first charging cycle and the second OCV value at a time point after a specified time after the end of the second charging cycle.

[0069] As another example, the calculation unit 132 can calculate the OCV difference between a first OCV value corresponding to a first discharge cycle and a second OCV value corresponding to a second discharge cycle following the first discharge cycle, within a time period of OCV data. In this case, the OCV value corresponding to each discharge cycle can be selected as the OCV value at a time point after a specified time (e.g., 2 hours) after the end of each discharge cycle. For example, the calculation unit 132 can calculate the OCV difference as the difference between the first OCV value at a time point after a specified time following the end of the first discharge cycle and the second OCV value at a time point after a specified time following the end of the second discharge cycle.

[0070] Reference Figure 2a and Figure 2b The graphs 210 and 220, which illustrate the OCV difference for the charging or discharging cycle of the battery cell to be diagnosed, calculated by the calculation unit 132, can be confirmed.

[0071] In Figures 210 and 220, the OCV difference corresponding to a specific charging cycle or a specific discharging cycle corresponds to each of the battery cells to be diagnosed, and can be the difference between the OCV value corresponding to a specific cycle and the OCV value corresponding to the immediately preceding cycle. For example, in Figure 210, the OCV difference of the battery cell to be diagnosed corresponding to the third charging cycle of the first battery cell can be the difference between the OCV value corresponding to the third charging cycle of the first battery cell and the OCV value corresponding to the second charging cycle of the first battery cell.

[0072] According to one embodiment, the normalization unit 133 can obtain a normalized OCV difference value by normalizing the OCV difference values ​​calculated by the calculation unit 132 for the plurality of battery cells 151, 153 and 155. For example, the normalization unit 133 can obtain a normalized OCV difference value by normalizing the OCV difference values ​​based on Equation 1 below.

[0073] [Formula 1]

[0074] In Equation 1 above, dOCV i dOCV is the OCV difference of the i-th battery cell (where i is a natural number) among multiple battery cells 151, 153, and 155. min It is the minimum OCV difference among multiple battery cells 151, 153, and 155, and dOCV max It is the maximum value of the OCV difference among multiple battery cells 151, 153 and 155.

[0075] Reference Figure 3 This can be illustrated by graph 300, which shows the normalized OCV difference for the charging cycle of the battery cell to be diagnosed, obtained by normalization unit 133. Specifically, graph 300 can be illustrated by normalization unit 133 based on... Figure 2a Chart 210 shows the normalized OCV difference obtained by normalizing the OCV difference of the battery cell to be diagnosed.

[0076] In Figure 300, the normalized OCV difference corresponding to a specific charging cycle corresponds to each of the battery cells to be diagnosed, and can be a value calculated by inputting the OCV difference of the battery cell to be diagnosed corresponding to a specific charging cycle into Equation 1 above. For example, in Figure 300, the normalized OCV difference of the battery cell to be diagnosed corresponding to the thirteenth charging cycle of the first battery cell can be a value calculated by inputting the OCV difference corresponding to the thirteenth charging cycle of the battery cell to be diagnosed, as well as the minimum and maximum values ​​of the OCV difference corresponding to the thirteenth charging cycle of the first battery cell, into Equation 1 above.

[0077] According to one embodiment, the identification unit 134 can identify suspected abnormal battery cells among the plurality of battery cells 151, 153 and 155 based on the normalized OCV difference values ​​of the plurality of battery cells 151, 153 and 155 obtained by the normalization unit 133.

[0078] According to one implementation, the identification unit 134 can identify suspected abnormal battery cells among a plurality of battery cells 151, 153, and 155 based on the deviation between normalized OCV differences. In this case, the deviation can be a value obtained by subtracting the smaller value from the larger value of two normalized OCV differences.

[0079] For example, when the deviation between the maximum and second largest values ​​in the normalized OCV difference is greater than or equal to a first threshold (e.g., 0.67), the identification unit 134 can identify the battery cell with the maximum value as a suspected abnormal battery cell. According to Figure 300, when the deviation 305 between the maximum value 301 and the second largest value 303 in the normalized OCV difference during the thirteenth charging cycle is greater than or equal to the first threshold, the identification unit 134 can identify the sixth battery cell with the maximum value 301 as a suspected abnormal battery cell.

[0080] As another example, when the deviation between the minimum and the second minimum value in the normalized OCV difference is greater than or equal to a second threshold (e.g., 0.8), the identification unit 134 can identify the battery cell with the minimum value as a suspected abnormal battery cell. According to Figure 300, when the deviation 315 between the minimum 311 and the second minimum 313 in the normalized OCV difference in the fourteenth charging cycle is greater than or equal to the second threshold, the identification unit 134 can identify the sixth battery cell with the minimum value 311 as a suspected abnormal battery cell.

[0081] According to one embodiment, the diagnostic unit 135 can diagnose the abnormality of a suspected abnormal battery cell based on the OCV deviation value between a second OCV value corresponding to a second charge / discharge cycle of a suspected abnormal battery cell identified by the identification unit 134 and a representative value of the second OCV value corresponding to the second charge / discharge cycles of a plurality of battery cells 151, 153, and 155. Here, the representative value can be selected as the average value or the median value of the second OCV values.

[0082] For example, according to Figure 300, the diagnostic unit 135 can calculate the OCV deviation value between the second OCV value of the sixth battery cell identified as a suspected abnormal battery cell and the representative values ​​of the second OCV values ​​of the first to eighth battery cells through Figure 210, and can diagnose the abnormality of the sixth battery cell based on the calculated OCV deviation value.

[0083] According to one embodiment, when the OCV deviation value of a suspected abnormal battery cell is greater than or equal to a third threshold, the diagnostic unit 135 can diagnose the suspected abnormal battery cell as an abnormal battery cell.

[0084] According to one embodiment, in addition to the abnormal battery cells diagnosed by the diagnostic unit 135, the battery diagnostic device 101 can repeat the operations of the calculation unit 132, the normalization unit 133, the identification unit 134 and the diagnostic unit 135 for the remaining battery cells at unit time intervals (e.g., charge / discharge cycles) until no abnormal battery cells are diagnosed.

[0085] Figure 4 This is a flowchart illustrating the operation of a battery diagnostic device according to one embodiment. It can be used... Figure 1 To explain the configuration Figure 4 .

[0086] Figure 4 The illustrated embodiment is merely one embodiment, and the order of operation according to various embodiments of the present invention may differ. Figure 4 The order shown can be omitted. Figure 4 Some of the operations shown can change the order of operations or can be combined.

[0087] Reference Figure 4 In operation 405, the battery diagnostic device 101 can acquire OCV data for multiple battery cells 151, 153, and 155. For example, the battery diagnostic device 101 can measure the voltage, current, and / or temperature of the multiple battery cells 151, 153, and 155 and generate OCV data based on the measured information. In this case, the battery diagnostic device 101 can use sensor 120 to measure the voltage, current, and / or temperature of the multiple battery cells 151, 153, and 155. As another example, the battery diagnostic device 101 can use communication circuit 110 to receive OCV data of the multiple battery cells 151, 153, and 155 generated by electronic device 102.

[0088] In operation 410, the battery diagnostic device 101 can calculate an OCV difference for each of the plurality of battery cells 151, 153, and 155 based on the OCV data acquired in operation 405. The OCV difference can be the difference between two corresponding OCV values ​​in each of two charge / discharge cycles within a plurality of charge / discharge cycles included in the time period of the OCV data. Here, a charge / discharge cycle can include a charge cycle and a discharge cycle.

[0089] According to one embodiment, the OCV difference can be the difference between a first OCV value corresponding to a first charge / discharge cycle in a plurality of charge / discharge cycles and a second OCV value corresponding to a second charge / discharge cycle in a plurality of charge / discharge cycles. In this case, the second charge / discharge cycle can be a cycle adjacent to the first charge / discharge cycle after the first charge / discharge cycle. Alternatively, the OCV difference can be a value obtained by subtracting the first OCV value from the second OCV value.

[0090] According to one embodiment, the battery diagnostic device 101 can calculate the OCV difference based on a type of charging cycle or discharging cycle included in the charging / discharging cycle.

[0091] As an example, the battery diagnostic device 101 can calculate the OCV difference between a first OCV value corresponding to a first charging cycle and a second OCV value corresponding to a second charging cycle following the first charging cycle, within a time period of OCV data. In this case, the OCV value corresponding to each charging cycle can be selected as the OCV value at a time point after a specified time (e.g., 2 hours) after the end of each charging cycle. For example, the battery diagnostic device 101 can calculate the OCV difference as the difference between the first OCV value at a time point after a specified time after the end of the first charging cycle and the second OCV value at a time point after a specified time after the end of the second charging cycle.

[0092] As another example, the battery diagnostic device 101 can calculate the OCV difference between a first OCV value corresponding to a first discharge cycle and a second OCV value corresponding to a second discharge cycle following the first discharge cycle, across multiple discharge cycles included in the OCV data time period. In this case, the OCV value corresponding to each discharge cycle can be selected as the OCV value at a time point after a specified time (e.g., 2 hours) following the end of each discharge cycle. For example, the battery diagnostic device 101 can calculate the OCV difference as the difference between the first OCV value at a time point after a specified time following the end of the first discharge cycle and the second OCV value at a time point after a specified time following the end of the second discharge cycle.

[0093] In operation 415, the battery diagnostic device 101 can obtain a normalized OCV difference value by normalizing the OCV difference values ​​calculated by the calculation unit 132 for the multiple battery cells 151, 153, and 155. For example, the battery diagnostic device 101 can obtain a normalized OCV difference value by normalizing the OCV difference value based on Equation 1 above.

[0094] In operation 420, the battery diagnostic device 101 can identify suspected abnormal battery cells among the multiple battery cells 151, 153 and 155 based on the normalized OCV difference values ​​of the multiple battery cells 151, 153 and 155 obtained in operation 415.

[0095] According to one embodiment, the battery diagnostic device 101 can identify suspected abnormal battery cells among a plurality of battery cells 151, 153, and 155 based on the deviation between normalized OCV differences. In this case, the deviation can be a value obtained by subtracting the smaller value from the larger value of two normalized OCV differences.

[0096] For example, when the deviation between the maximum and the second largest value in the normalized OCV difference is greater than or equal to a first threshold (e.g., 0.67), the battery diagnostic device 101 can identify the battery cell with the maximum value as a suspected abnormal battery cell.

[0097] As another example, when the deviation between the minimum and the second minimum value in the normalized OCV difference is greater than or equal to a second threshold (e.g., 0.8), the battery diagnostic device 101 can identify the battery cell with the minimum value as a suspected abnormal battery cell.

[0098] In operation 425, the battery diagnostic device 101 can diagnose the anomaly of the suspected abnormal battery cell identified in operation 420. According to one embodiment, the battery diagnostic device 101 can diagnose the anomaly of the suspected abnormal battery cell based on the OCV deviation value between a second OCV value corresponding to a second charge / discharge cycle of the suspected abnormal battery cell and a representative value of the second OCV values ​​corresponding to the second charge / discharge cycles of the plurality of battery cells 151, 153, and 155. Here, the representative value can be selected as the average value or the median value of the second OCV values.

[0099] According to one embodiment, when the OCV deviation value of a suspected abnormal battery cell is greater than or equal to a third threshold, the battery diagnostic device 101 can diagnose the suspected abnormal battery cell as an abnormal battery cell.

[0100] According to one embodiment, in addition to the abnormal battery cells diagnosed in operation 425, the battery diagnostic device 101 can repeat operations 410 to 425 for the remaining battery cells at unit time intervals (e.g., charge / discharge cycles) until no abnormal battery cells are diagnosed.

[0101] Unless otherwise specified, the terms “comprising,” “configured,” or “having” above mean that they may include the corresponding components 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 to which the embodiments disclosed in this document pertain. Unless expressly defined in this document, commonly used terms (such as those defined in dictionaries) should be interpreted as consistent with the meaning in the context of the relevant art and should not be interpreted in an idealized or overly formal sense.

Claims

1. A battery diagnostic device, the battery diagnostic device comprising: The acquisition unit acquires open-circuit voltage (OCV) data of multiple battery cells; The calculation unit calculates, based on the OCV data, the OCV difference between a first OCV value corresponding to a first charge / discharge cycle and a second OCV value corresponding to a second charge / discharge cycle following the first charge / discharge cycle for each of the plurality of battery cells; A normalization unit obtains a normalized OCV difference value by normalizing the OCV difference value of the plurality of battery cells. An identification unit identifies suspected abnormal battery cells among the plurality of battery cells based on the normalized OCV difference. as well as The diagnostic unit diagnoses the abnormality of the suspected abnormal battery cell based on the OCV deviation value between the second OCV value of the identified suspected abnormal battery cell and the representative value of the second OCV value of the plurality of battery cells.

2. The battery diagnostic device according to claim 1, wherein, The normalization unit normalizes the OCV difference values ​​of the plurality of battery cells based on Equation 1 below to obtain the normalized OCV difference value. [Formula 1] (In Equation 1, dOCV) i dOCV is the OCV difference of the i-th battery cell among the plurality of battery cells. min It is the minimum value among the OCV differences of the plurality of battery cells, and dOCV max It is the maximum value among the OCV differences of the plurality of battery cells.

3. The battery diagnostic device according to claim 1, wherein, The identification unit identifies the suspected abnormal battery cells among the plurality of battery cells based on the deviation between the normalized OCV differences.

4. The battery diagnostic device according to claim 3, wherein, When the deviation between the maximum value and the second largest value in the normalized OCV difference is greater than or equal to the first threshold, the identification unit identifies the battery cell with the maximum value as the suspected abnormal battery cell.

5. The battery diagnostic device according to claim 3, wherein, When the deviation between the minimum value and the second minimum value in the normalized OCV difference is greater than or equal to the second threshold, the identification unit identifies the battery cell with the minimum value as the suspected abnormal battery cell.

6. The battery diagnostic device according to claim 1, wherein, When the OCV deviation value of the suspected abnormal battery cell is greater than or equal to the third threshold, the diagnostic unit diagnoses the suspected abnormal battery cell as an abnormal battery cell.

7. The battery diagnostic device according to claim 1, wherein, The first OCV value is the OCV value corresponding to the charging cycle included in the first charge / discharge cycle, and the second OCV value is the OCV value corresponding to the charging cycle included in the second charge / discharge cycle.

8. The battery diagnostic device according to claim 1, wherein, The first OCV value is the OCV value corresponding to the discharge cycle included in the first charge / discharge cycle, and the second OCV value is the OCV value corresponding to the discharge cycle included in the second charge / discharge cycle.

9. A method for operating a battery diagnostic device, the method comprising: The operation of acquiring the open-circuit voltage (OCV) data of multiple battery cells; Based on the OCV data, the operation of calculating the OCV difference between the first OCV value corresponding to the first charge / discharge cycle and the second OCV value corresponding to the second charge / discharge cycle after the first charge / discharge cycle for each of the plurality of battery cells; The operation of obtaining normalized OCV difference values ​​by normalizing the OCV difference values ​​of the multiple battery cells; The operation of identifying suspected abnormal battery cells among the multiple battery cells based on the normalized OCV difference; as well as The abnormal operation of the suspected abnormal battery cell is diagnosed based on the OCV deviation value between the second OCV value of the identified suspected abnormal battery cell and the representative value of the second OCV value of the plurality of battery cells.

10. The operating method according to claim 9, wherein, The operation of obtaining the normalized OCV difference includes normalizing the OCV difference of the plurality of battery cells based on Equation 1 below. [Formula 1] (In Equation 1, dOCV) i dOCV is the OCV difference of the i-th battery cell among the plurality of battery cells. min It is the minimum value among the OCV differences of the plurality of battery cells, and dOCV max It is the maximum value among the OCV differences of the plurality of battery cells.

11. The operating method according to claim 9, wherein, The operation of identifying the suspected abnormal battery cell includes identifying the suspected abnormal battery cell among the plurality of battery cells based on the deviation between the normalized OCV differences.

12. The operating method according to claim 11, wherein, The operation of identifying the suspected abnormal battery cell includes identifying the battery cell with the maximum value as the suspected abnormal battery cell when the deviation between the maximum value and the second largest value in the normalized OCV difference is greater than or equal to a first threshold.

13. The operating method according to claim 11, wherein, The operation of identifying the suspected abnormal battery cell includes identifying the battery cell with the minimum value as the suspected abnormal battery cell when the deviation between the minimum value and the second minimum value in the normalized OCV difference is greater than or equal to the second threshold.

14. The operating method according to claim 9, wherein, The operation of diagnosing the abnormality of the suspected abnormal battery cell includes diagnosing the suspected abnormal battery cell as an abnormal battery cell when the OCV deviation value of the suspected abnormal battery cell is greater than or equal to a third threshold.

15. The operating method according to claim 9, wherein, The first OCV value is the OCV value corresponding to the charging cycle included in the first charge / discharge cycle, and the second OCV value is the OCV value corresponding to the charging cycle included in the second charge / discharge cycle.

Images