Battery diagnosis device and method

Abstract

According to one embodiment disclosed in the present document, a battery diagnosis device may comprise: an interface unit which obtains the SOC after charging for each charging cycle for each of a plurality of battery cells; and one or more processors which calculate the charge amount relative to the average for each of the plurality of battery cells, on the basis of the SOC after charging, calculate the degree of change in the charge amount relative to the average according to the charging cycle of each of the plurality of battery cells, calculate an index value by applying a weight for each cycle to the degree of change in the charge amount relative to the average of a battery cell, among the plurality of battery cells, which is undergoing diagnosis, and diagnose an abnormality in the battery cell undergoing diagnosis on the basis of the index values for each cycle of the battery cell undergoing diagnosis.

Description

Battery diagnostic device and method

[0001] Cross-citation with related applications

[0002] This application claims the benefit of priority from Republic of Korea Patent Application No. 10-2024-0054760, filed April 24, 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 method.

[0005] Recently, research and development on secondary batteries has been actively conducted. Here, secondary batteries are rechargeable and include both conventional Ni / Cd and Ni / MH batteries, as well as recent lithium-ion batteries. Among secondary batteries, lithium-ion batteries have the advantage of having a much 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 suitable for use as power sources for mobile devices. Recently, their use has expanded to include power sources for electric vehicles, attracting 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] Typically, diagnosing abnormal voltage behavior caused by battery cell tab disconnection, etc., is a key component of battery cell abnormality diagnosis. However, conventional voltage abnormality diagnosis methods have limitations in detecting minute voltage fluctuations.

[0012] One purpose of the embodiments disclosed in this document is to provide a battery diagnosis device and method capable of effectively diagnosing abnormalities in battery cells by defining the average charge amount of each battery cell based on the SOC after charging of the battery cells and analyzing the average charge amount to detect minute voltage changes.

[0013] 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.

[0014] According to an embodiment disclosed in the present document, a battery diagnosis device may include an interface unit that obtains a post-charge SOC for each charging cycle for each of a plurality of battery cells, and one or more processors that calculate an average charge amount of each of the plurality of battery cells based on the post-charge SOC, calculate a degree of change in the average charge amount according to the charging cycle of each of the plurality of battery cells, apply a cycle-by-cycle weight to a degree of change in the average charge amount of a diagnosis target battery cell among the plurality of battery cells to calculate an index value, and diagnose an abnormality of the diagnosis target battery cell based on the cycle-by-cycle index values ​​of the diagnosis target battery cell.

[0015] According to an embodiment, the interface unit can obtain, for each of the plurality of battery cells, an SOC after a specified time has elapsed after each charging cycle ends.

[0016] According to an embodiment, the processor may calculate an average SOC after charging of each of the plurality of battery cells for each charging cycle, calculate an overall cycle average based on the calculated average SOCs after charging for each charging cycle, and calculate a charge amount relative to the average based on the SOC after charging, the average SOC after charging, and the overall cycle average.

[0017] According to an embodiment, the processor may calculate a difference value between an average charge amount in a first charging cycle among a plurality of charging cycles and an average charge amount in a second charging cycle prior to the first charging cycle as a degree of change in the average charge amount corresponding to the first charging cycle.

[0018] According to an embodiment, the processor may calculate an average change degree representing an average of the change degrees of charge amount compared to an average in a first charging cycle of the remaining battery cells other than the battery cell to be diagnosed among the plurality of battery cells, identify a minimum change degree representing a minimum value among the change degrees of charge amount compared to an average in the first charging cycle of the remaining battery cells, and multiply a larger value of the average change degree and the minimum change degree by the change degree of charge amount compared to an average in the first charging cycle of the battery cell to be diagnosed to calculate a weight in the first charging cycle.

[0019] According to an embodiment, the processor may divide the degree of change in the charge amount compared to the average in the first charging cycle of the battery cell to be diagnosed by a weight in the first charging cycle to calculate an index value corresponding to the first charging cycle.

[0020] According to an embodiment, the processor can diagnose an abnormality in the battery cell to be diagnosed by comparing the maximum value and a threshold value among the cycle-by-cycle indicator values ​​of the battery cell to be diagnosed.

[0021] According to an embodiment disclosed in the present document, a battery diagnosis method may include a step of obtaining a post-charge SOC for each charging cycle for each of a plurality of battery cells, a step of calculating an average charge amount of each of the plurality of battery cells based on the post-charge SOC, a step of calculating a degree of change in the average charge amount of each of the plurality of battery cells according to the charging cycle, a step of calculating an index value by applying a cycle-by-cycle weight to a degree of change in the average charge amount of a battery cell to be diagnosed among the plurality of battery cells, and a step of diagnosing an abnormality of the battery cell to be diagnosed based on the cycle-by-cycle index values ​​of the battery cell to be diagnosed.

[0022] According to an embodiment, the step of obtaining the SOC after charging may be characterized by obtaining the SOC after a specified time has elapsed after each charging cycle is completed, for each of the plurality of battery cells.

[0023] According to an embodiment, the step of calculating the average charge amount of each of the plurality of battery cells may include the step of calculating the average SOC after charging of each of the plurality of battery cells for each charging cycle, the step of calculating the overall cycle average based on the calculated average SOCs after charging for each charging cycle, and the step of calculating the average charge amount based on the post-charge SOC, the average SOC after charging, and the overall cycle average.

[0024] According to an embodiment, the step of calculating the degree of change in the average charge amount may be characterized by calculating a difference value between the average charge amount in a first charging cycle among a plurality of charging cycles and the average charge amount in a second charging cycle prior to the first charging cycle as the degree of change in the average charge amount corresponding to the first charging cycle.

[0025] According to an embodiment, the step of calculating the index value may include the step of calculating an average change degree representing an average of the change degrees of the amount of charge compared to the average in the first charging cycle of the remaining battery cells other than the battery cell to be diagnosed among the plurality of battery cells, the step of identifying a minimum change degree representing a minimum value among the change degrees of the amount of charge compared to the average in the first charging cycle of the remaining battery cells, the step of calculating a weight in the first charging cycle by multiplying a larger value between the average change degree and the minimum change degree by the change degree of the amount of charge compared to the average in the first charging cycle of the battery cell to be diagnosed, and the step of calculating an index value corresponding to the first charging cycle by dividing the change degree of the amount of charge compared to the average in the first charging cycle of the battery cell to be diagnosed by the weight in the first charging cycle.

[0026] According to an embodiment, the step of diagnosing an abnormality of the diagnostic battery cell may be characterized by diagnosing an abnormality of the diagnostic battery cell by comparing a maximum value and a threshold value among cycle-by-cycle indicator values ​​of the diagnostic battery cell.

[0027] The battery diagnosis device and method according to the embodiments disclosed in this document can effectively diagnose abnormalities in battery cells by defining the average charge amount of the battery cell based on the SOC after charging.

[0028] In addition, various effects may be provided, either directly or indirectly, through this document.

[0029] FIG. 1 is a block diagram showing the configuration of a battery diagnostic device according to one embodiment disclosed in this document.

[0030] FIG. 2 is a diagram showing an example of obtaining SOC after charging according to one embodiment disclosed in this document.

[0031] FIGS. 3A to 3E are diagrams showing examples of a process for diagnosing a battery according to one embodiment disclosed in this document.

[0032] FIG. 4 is a diagram showing an example of a process for calculating an index value from SOC data after charging according to one embodiment disclosed in this document.

[0033] FIGS. 5 to 7 are flowcharts illustrating a battery diagnosis method according to one embodiment disclosed in this document.

[0034] FIG. 8 is a block diagram showing the hardware configuration of a computing system for performing an operating method of a battery diagnostic device according to one embodiment disclosed in this document.

[0035] 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.

[0036] In this document, the singular form of a noun corresponding to an item may include one or more of said items, unless the context clearly indicates otherwise. In this document, phrases such as "A or B," "at least one of A and B," "at least one of A or B," "A, B, or C," "at least one of A, B, and C," and "at least one of A, B, or C" may each include any one of the items listed together in that phrase, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" 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). When a component (e.g., a first component) is referred to as being “coupled” or “connected” to another component (e.g., a second component), with or without the terms “functionally” or “communicatively,” it means that the component can be connected to the other component directly (e.g., wired), wirelessly, or through a third component.

[0037] Each component (e.g., a module or a program) described in this document may include one or more entities. According to various embodiments, one or more components or operations of the 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 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.

[0038] The term "module" or "part" used in this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit. A module may be an integral component, or a minimum unit or part of such a component that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0039] Various embodiments of the present document may be implemented as software (e.g., a program or an application) including one or more instructions stored in a machine-readable storage medium (e.g., memory). For example, a processor of the device may call at least one instruction among the one or more instructions stored from the storage medium and execute it. This enables the device to operate to perform at least one function according to the at least one instruction called. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, "non-transitory" only means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic waves), and this term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily in the storage medium.

[0040]

[0041] FIG. 1 is a block diagram showing the configuration of a battery diagnostic device according to one embodiment disclosed in this document.

[0042] Referring to FIG. 1, a battery diagnostic device (100) may include an interface unit (110) and one or more processors (120).

[0043] The battery diagnostic device (100) can diagnose whether a battery cell to be diagnosed is abnormal by analyzing the SOC of a plurality of battery cells. More specifically, the battery diagnostic device (100) can define the average charge amount based on the SOC of the battery cell, and by analyzing the average charge amount, can detect minute voltage changes in the battery cell, and accordingly, can effectively diagnose whether there is an abnormality such as a tab open circuit that causes minute voltage changes.

[0044] The operation of the battery diagnostic device (100) below can be performed by a battery management system (BMS) within a vehicle, a battery BMS provided within a battery pack, and can also be performed in various devices such as a server, cloud, charger, or charger / discharger.

[0045] The interface unit (110) establishes a connection between the battery diagnostic device (100) and an electronic device (e.g., a server, a BMS of a battery pack, a vehicle BMS, etc.), and can transmit and receive data through the established connection. The connection between the interface unit (110) and the electronic device 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, WiFi (wireless fidelity), or IrDA (infrared data association)), or a long-range communication network (cellular network, 4G network, 5G network).

[0046] According to another embodiment, the connection between the battery diagnostic device (100) and the electronic device 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] The interface unit (110) can obtain information on multiple battery cells. The multiple battery cells may be cells provided in the same battery pack, module, or bank.

[0048] In one embodiment, when the battery diagnostic device (100) is implemented as a separate component from the electronic device (e.g., a server external to the electronic device), the interface unit (110) can obtain information on battery cells through a communication channel established between the battery diagnostic device (100) and the electronic device.

[0049] In another embodiment, when the battery diagnostic device (100) is implemented as a BMS in an electronic device, the interface unit (110) can obtain information on the battery cells from at least one sensor that can measure information related to the status of the battery cells (e.g., voltage, current, temperature, etc.).

[0050] The interface unit (110) can obtain the SOC after each charging cycle of each battery cell. For example, if 10 charging cycles are performed for each battery cell, the interface unit (110) can obtain data on the SOC after 10 charging cycles for each battery cell.

[0051] According to an embodiment, the interface unit (110) can obtain the SOC for each of the plurality of battery cells after a specified time has elapsed after each charging cycle ends.

[0052] Since voltage fluctuations in battery cells may occur immediately after charging is completed, the SOC of the battery cells can be acquired after the charging cycle has ended and the voltage has stabilized to obtain a more accurate SOC value. To this end, the interface unit (110) can acquire the SOC of each battery cell at a specified time point after the charging cycle ends. For example, the specified time can be set to a time sufficient for the voltage to stabilize, such as 2 hours.

[0053] For example, the interface unit (110) can obtain the SOC at a point in time (T) after a specified time has passed from the point in time (C_E) at which the charging cycle of the battery cell ends, as illustrated in FIG. 2. In FIG. 2, the x-axis represents time, the y-axis represents voltage, and chgSOC conceptually represents obtaining the SOC after charging at the indicated point in time. That is, the battery diagnostic device (100) can identify the point in time for obtaining the SOC after charging from the voltage data of the battery cell over time.

[0054] In addition to the SOC after charging, the interface unit (110) can also obtain additional information related to the battery, such as the voltage, temperature, and SOH of the battery cell.

[0055] The processor (120) may be implemented as one or more processors. Each processor 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.

[0056] The processor (120) can diagnose an abnormality in the battery cell to be diagnosed and / or each battery cell by using the SOC of the battery cells obtained by the interface unit (110) after charging. For example, the processor (120) can diagnose an abnormality in the battery cell by detecting a minute voltage fluctuation in each battery cell by analyzing the SOC of each battery cell after charging.

[0057] The functions and operations of the battery diagnostic device (100) described below may be performed by a single processor, or each function may be separated and performed by at least some of the processors. For convenience of explanation, the operation of the battery diagnostic device (100) will be described below as being performed by a single processor.

[0058] FIGS. 3A to 3E are diagrams showing examples of a process for diagnosing a battery according to one embodiment disclosed in this document.

[0059] Hereinafter, the operation of the battery diagnostic device (100) will be described in detail with reference to FIGS. 3a to 3e.

[0060] First, the interface unit (110) can obtain the SOC after charging for each battery cell in each charging cycle, as exemplarily illustrated in the graph (310) of FIG. 3A. The graph (310) shows the SOC data after charging obtained when each of eight battery cells (C1 to C8) has undergone 17 charging cycles (0 to 16), with the x-axis representing the cycle number and the y-axis representing the SOC after charging. The graphs illustrated in FIGS. 3B to 3E below illustrate values ​​calculated based on the SOC after charging shown in the graph (310) of FIG. 3A.

[0061] The processor (120) may calculate an average charge amount for each of the plurality of battery cells based on the SOC after charging. Here, the average charge amount may be a parameter defined to compare the relative charge amounts of each battery cell in each charging cycle. The processor (120) may calculate an average charge amount representing the relative charge amount for each battery cell to detect relative micro-behavior of the battery cell to be diagnosed compared to other battery cells.

[0062] According to an embodiment, the processor (120) may calculate the average SOC after charging of each of the plurality of battery cells for each charging cycle. The processor (120) may calculate the average SOC after charging by averaging the SOCs after charging of the battery cells obtained in each charging cycle based on each charging cycle. For example, if 10 charging cycles are performed for each battery cell, the processor (120) may calculate the average SOC after charging for each charging cycle, thereby calculating the average SOC data after 10 charges.

[0063] The processor (120) can calculate an overall cycle average based on the average SOCs after charging calculated for each charging cycle. The processor (120) can calculate an overall cycle average by averaging the average SOCs after charging.

[0064] The processor (120) can calculate the average charge amount based on the SOC after charging, the average SOC after charging, and the average of the entire cycle. The processor (120) can convert the SOC after charging of each battery cell into the average charge amount using the average SOC after charging and the average of the entire cycle.

[0065] In one embodiment, the processor (120) can calculate the average charge amount of each battery cell based on [Mathematical Formula 1] below.

[0066] [Mathematical Formula 1]

[0067]

[0068] Here, is the average charge amount in each charging cycle of each battery cell, chgSOC is the SOC after charging in each charging cycle of each battery cell, avg is the average SOC after charging, and norm is the average of the entire cycle.

[0069] In this way, the processor (120) can derive the relative charge amount of each battery cell. The average charge amount of each battery cell calculated by the processor (120) is exemplarily illustrated in the graph (320) of FIG. 3B. In FIG. 3B, the y-axis represents the charge amount relative to the average.

[0070] Comparing the circled portion of the graph (320), it can be seen that the average charge amount can more clearly compare the relative charge of each battery cell compared to the graph (310) showing the SOC after charging of each battery cell.

[0071] The processor (120) can calculate the degree of change in the average charge amount according to each charging cycle of each of the plurality of battery cells. The processor (120) can calculate the degree of change in the average charge amount according to the charging cycle from the average charge amount of each battery cell.

[0072] According to an embodiment, the processor (120) may calculate a difference value between the average charge amount in a first charging cycle among a plurality of charging cycles and the average charge amount in a second charging cycle prior to the first charging cycle as a degree of change in the average charge amount corresponding to the first charging cycle. In this case, the difference value between the average charge amount in the first charging cycle and the average charge amount in the second charging cycle may mean an absolute value.

[0073] The interval between the first charging cycle and the second charging cycle may be preset. For example, the first charging cycle and the second charging cycle may be adjacent cycles. In another example, the interval between the first charging cycle and the second charging cycle may be n cycle intervals (where n is an integer greater than or equal to 2). For example, if the first charging cycle is the mth cycle (where m is an integer greater than or equal to 2), the second charging cycle may be the m-2th cycle.

[0074] In this way, the processor (120) can apply the difference value between the average charge amount in the first charging cycle and the second charging cycle to all battery cells and cycles. The degree of change in the average charge amount calculated by the processor (120) is exemplarily illustrated in the graph (330) of FIG. 3C. The degree of change in the average charge amount in the graph (330) of FIG. 3C represents the result when n=2 in the average charge amount in the graph (320). For example, in FIG. 3C, the y-axis represents the degree of change in the average charge amount, and it can be confirmed that the C3 cell has a relatively large degree of change in the charge amount compared to other cells.

[0075] The processor (120) may calculate an index value by applying a weighting factor for each cycle to the degree of change in the charge amount of a battery cell to be diagnosed compared to the average among a plurality of battery cells. At this time, the index value may be a value that serves as a reference for the processor (120) to diagnose an abnormality in the battery cell to be diagnosed. The processor (120) may calculate the index value from the degree of change in the charge amount compared to the average in order to detect micro-voltage fluctuations based on the change in the charge amount of the battery cell.

[0076] According to an embodiment, the processor (120) can calculate a weight to be applied to a battery cell to be diagnosed from data on the degree of change in the amount of charge compared to the average of the battery cells.

[0077] To this end, first, the processor (120) can calculate an average change degree representing an average of the change degrees of charge amount compared to the average in the first charging cycle of the remaining battery cells other than the battery cell to be diagnosed among a plurality of battery cells, and can identify a minimum change degree representing a minimum value among the change degrees of charge amount compared to the average in the first charging cycle of the remaining battery cells other than the battery cell to be diagnosed.

[0078] The processor (120) may calculate a weight to be applied to the battery cell to be diagnosed based on the average degree of change and the minimum degree of change data. In one embodiment, the processor (120) may calculate the weight in the first charging cycle by multiplying the greater value of the average degree of change and the minimum degree of change by the average-to-charge amount change in the first charging cycle of the battery cell to be diagnosed.

[0079] The processor (120) can calculate an index value for each battery cell using the calculated weights. According to an embodiment, the processor (120) can calculate an index value corresponding to the first charging cycle by dividing the degree of change in the charge amount compared to the average in the first charging cycle of the battery cell to be diagnosed by the weight in the first charging cycle. In this case, the index value can reflect the ratio of the change amount of the battery cell to be diagnosed compared to other cells.

[0080] The index values ​​produced by the processor (120) are exemplarily illustrated in the graph (340) of FIG. 3d. In the graph (340), the y-axis represents the index values, and it can be confirmed that the tendencies of each battery cell are distinctly different, and it can be confirmed that the relative degree of change in the C3 cell is distinctly different from that of other cells.

[0081] The processor (120) can diagnose an abnormality in a battery cell to be diagnosed based on the cycle-by-cycle indicator values ​​of the battery cell to be diagnosed. As described above, the calculated indicator values ​​reflect the relative voltage change characteristics between battery cells, so the processor (120) can use the indicator values ​​to detect minute voltage changes in the battery cell to be diagnosed and diagnose an abnormality.

[0082] According to an embodiment, the processor (120) can diagnose an abnormality in the battery cell to be diagnosed by comparing the maximum value among the cycle-by-cycle indicator values ​​of the battery cell to be diagnosed with a threshold value. For example, if the maximum value among the indicator values ​​of the battery cell to be diagnosed exceeds the threshold value, the processor (120) can diagnose the battery cell to be diagnosed as abnormal. Since a large maximum value among the indicator values ​​of the battery cell to be diagnosed can be regarded as a large voltage fluctuation compared to other cells, the processor (120) can diagnose an abnormality in the battery cell by comparing the maximum value among the indicator values ​​with the threshold value.

[0083] The processor (120) can identify the maximum value of the indicator values ​​of each battery cell and compare it with a threshold value, as shown in the graph (350) in FIG. 3e. Referring to the graph (350), since the maximum value of the indicator values ​​of cell C3 exceeds the threshold value, the processor (120) can diagnose cell C3 as abnormal.

[0084] FIG. 4 is a diagram showing an example of a process for calculating an index value from SOC data after charging according to one embodiment disclosed in this document.

[0085] Referring to FIG. 4, an example of a process in which a processor (120) analyzes data obtained from an interface unit (110) to diagnose each battery cell can be confirmed.

[0086] First, the interface unit (110) can obtain / store the SOC after charging obtained for each cycle of each battery cell in the form of a matrix, as illustrated in 410 of FIG. 4. In the matrix (410) of FIG. 4, each row represents a battery cell, each column represents a cycle, and each element of the matrix represents a SOC value after charging.

[0087] The processor (120) can calculate the average SOC after charging by averaging the SOC after charging of all battery cells for each cycle, and the average SOC after charging calculated from the matrix (410) is shown as a matrix (420). That is, the processor (120) can calculate the matrix (420) through a process of averaging the elements of each column in the matrix (410).

[0088] The processor (120) can calculate the overall cycle average by averaging the average SOCs after charging of each charging cycle, and the overall cycle average calculated from the matrix (420) is expressed as a norm. That is, the processor (120) can calculate the overall cycle average by averaging all elements of the matrix (420).

[0089] The processor (120) can calculate the average charge amount of each battery cell based on the SOC after charging, the average SOC after charging, and the average of the entire cycle, and an example thereof is shown in the matrix (430). At this time, the matrix sizes of the matrix (410) and the matrix (430) may be the same.

[0090] The processor (120) can calculate the degree of change in the average charge amount according to each charging cycle of the battery cells, and an example thereof is shown in the matrix (440). The matrix (440) represents the result when the cycle interval is 2 units in the average charge amount matrix (430), and as a result, it can be confirmed that the number of columns (15) of the matrix (440) is 2 less than the number of columns (17) of the matrix (430).

[0091] The processor (120) can calculate an index value for each charging cycle of each battery cell by applying a weight based on the degree of change in the amount of charge compared to the average, and an example thereof is shown in the matrix (450).

[0092] Thereafter, the processor (120) can identify the maximum value among the indicator values ​​for each battery cell. For example, the processor (120) can identify the maximum value of the indicator values ​​for each row of the matrix (450) to derive the matrix (460). The processor (120) can diagnose an abnormality in the battery cell by comparing the identified maximum value with a threshold value using the matrix (460).

[0093] FIGS. 5 to 7 are flowcharts illustrating a battery diagnosis method according to one embodiment disclosed in this document.

[0094] Referring to FIG. 5, the battery diagnosis method may include a step (S100) of obtaining a post-charge SOC for each charging cycle for each of a plurality of battery cells, a step (S200) of calculating an average charge amount of each of the plurality of battery cells based on the post-charge SOC, a step (S300) of calculating a degree of change in the average charge amount of each of the plurality of battery cells according to the charging cycle, a step (S400) of calculating an index value by applying a weight for each cycle to a degree of change in the charge amount of a battery cell to be diagnosed among the plurality of battery cells compared to the average, and a step (S500) of diagnosing an abnormality of the battery cell to be diagnosed based on the index values ​​for each cycle of the battery cell to be diagnosed.

[0095] In step S100, the interface unit (110) can obtain the SOC after charging for each of the plurality of battery cells for each charging cycle. In one embodiment, the interface unit (110) can obtain the SOC for each of the plurality of battery cells after a specified time has elapsed after each charging cycle ends.

[0096] At step S200, one or more processors (120) can calculate the average charge amount of each of the plurality of battery cells.

[0097] Referring to FIG. 6, a method for calculating an average charge amount by a processor (120) according to one embodiment may include a step (S210) of calculating an average SOC after charging of each of a plurality of battery cells for each charging cycle, a step (S220) of calculating an overall cycle average based on the average SOCs after charging calculated for each charging cycle, and a step (S230) of calculating an average charge amount based on the SOC after charging, the average SOC after charging, and the overall cycle average.

[0098] At step S210, the processor (120) can calculate the average SOC after charging by averaging the SOC after charging of multiple battery cells in each charging cycle.

[0099] At step S220, the processor (120) can re-average the post-charge average SOC calculated in each charging cycle to calculate the overall cycle average.

[0100] At step S230, the processor (120) may calculate the average charge amount based on the SOC after charging, the average SOC after charging, and the average of the entire cycle. In one embodiment, the processor (120) may calculate the average charge amount based on the above [Mathematical Formula 1].

[0101] In step S300, the processor (120) may calculate the degree of change in the average charge amount according to the charging cycle of each of the plurality of battery cells. In one embodiment, the processor (120) may calculate the difference value between the average charge amount in a first charging cycle among the plurality of charging cycles and the average charge amount in a second charging cycle prior to the first charging cycle as the degree of change in the average charge amount corresponding to the first charging cycle.

[0102] At step S400, the processor (120) can calculate an index value by applying a cycle-by-cycle weight to the degree of change in the charge amount compared to the average of the battery cell to be diagnosed.

[0103] Referring to FIG. 7, a method for calculating an index value by a processor (120) according to an embodiment may include a step (S410) of calculating an average change degree representing an average of the change degrees of charge amount compared to an average in a first charging cycle of the remaining battery cells other than a battery cell to be diagnosed among a plurality of battery cells, a step (S420) of identifying a minimum change degree representing a minimum value among the change degrees of charge amount compared to an average in the first charging cycle of the remaining battery cells, a step (S430) of calculating a weight in the first charging cycle by multiplying a larger value among the average change degree and the minimum change degree by the change degree of charge amount compared to an average in the first charging cycle of the battery cell to be diagnosed, and a step (S440) of calculating an index value corresponding to the first charging cycle by dividing the change degree of charge amount compared to an average in the first charging cycle of the battery cell to be diagnosed by the weight in the first charging cycle.

[0104] In step S410, the processor (120) can calculate an average change degree by averaging the change degrees of the charge amount compared to the average in the first charging cycle of the remaining battery cells other than the battery cell to be diagnosed.

[0105] At step S420, the processor (120) can identify a minimum change degree that represents the minimum value among the changes in the charge amount compared to the average of the remaining battery cells other than the battery cell to be diagnosed.

[0106] At step S430, the processor (120) can multiply the average change degree and the minimum change degree by a larger value among the average change degree and the minimum change degree to calculate a weight in the first charging cycle of the battery cell to be diagnosed.

[0107] At step S440, the processor (120) can divide the average change in charge amount in the first charging cycle of the battery cell to be diagnosed by the weight to calculate an index value corresponding to the first charging cycle.

[0108] In this way, the processor (120) can calculate an indicator value for each cycle of the battery cell to be diagnosed.

[0109] In step S500, the processor (120) can diagnose an abnormality in the battery cell to be diagnosed based on the cycle-by-cycle indicator values ​​of the battery cell to be diagnosed. In one embodiment, the processor (120) can diagnose an abnormality in the battery cell to be diagnosed by comparing the maximum value among the cycle-by-cycle indicator values ​​of the battery cell to be diagnosed with a threshold value. For example, if the maximum value among the indicator values ​​of the battery cell to be diagnosed exceeds the threshold value, the processor (120) can diagnose the battery cell to be diagnosed as abnormal.

[0110] FIG. 8 is a block diagram showing the hardware configuration of a computing system for performing an operating method of a battery diagnostic device according to one embodiment disclosed in this document.

[0111] Referring to FIG. 8, a computing system (1000) according to one embodiment disclosed in the present document may include an MCU (1010), a memory (1020), an input / output I / F (1030), and a communication I / F (1040).

[0112] The MCU (1010) may be a processor that executes various programs stored in the memory (1020), processes various information including time series data of the battery through these programs, and performs the functions of the processor included in the battery diagnostic device shown in the aforementioned FIG. 1.

[0113] The memory (1020) can store various programs for performing the functions of the battery diagnostic device. In addition, the memory (1020) can store various information, including battery data (such as SOC after charging) and diagnostic prediction results.

[0114] Such memories (1020) may be provided in multiple numbers as needed. The memories (1020) may be volatile memories or non-volatile memories. As volatile memories (1020), RAM, DRAM, SRAM, etc. may be used. As non-volatile memories (1020), ROM, PROM, EAROM, EPROM, EEPROM, flash memories, etc. may be used. The examples of the memories (1020) listed above are merely examples and are not limited to these examples.

[0115] The input / output I / F (1030) can provide an interface that enables data transmission and reception between an input device (not shown) such as a keyboard, mouse, or touch panel, and an output device (not shown) such as a display and the MCU (1010).

[0116] The communication I / F (1040) is a component capable of transmitting and receiving various data with a server, and may be any device capable of supporting wired or wireless communication. For example, a battery diagnostic device can transmit and receive various information, including battery data, from a separately provided external server via the communication I / F (1040).

[0117] In this way, a computer program according to one embodiment disclosed in this document may be implemented as a module that is recorded in a memory (1020) and processed by an MCU (1010) to perform each function illustrated in FIG. 1, for example.

[0118]

[0119] Although all components constituting the embodiments disclosed in this document have been described as being combined or operating in combination as one, the embodiments disclosed in this document are not necessarily limited to such embodiments. That is, within the scope of the purpose of the embodiments disclosed in this document, all of the components may be selectively combined and operated one or more times.

[0120] In addition, terms such as "include," "comprise," or "have" described above, unless specifically stated otherwise, mean that the corresponding component can be included, and therefore should be interpreted to include other components rather than excluding 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 belong, unless otherwise defined. Commonly used terms, such as terms defined in a dictionary, should be interpreted to be consistent with the contextual meaning of the relevant technology, and shall not be interpreted in an idealized or overly formal sense, unless explicitly defined in this document.

[0121] The above description is merely an example of the technical idea disclosed in this document, and those skilled in the art to which the embodiments disclosed in this document pertain may make various modifications and variations without departing from the essential characteristics of the embodiments disclosed in this document. Therefore, the embodiments disclosed in this document are not intended to limit the technical idea of ​​the embodiments disclosed in this document, but to explain it, and the scope of the technical idea disclosed in this document is not limited by these embodiments. The scope of protection of the technical idea disclosed in this document should be interpreted by the claims below, and all technical ideas within a scope equivalent thereto should be interpreted as being included in the scope of rights of this document.

Claims

1. An interface unit for obtaining the SOC after charging for each of the plurality of battery cells at each charging cycle; and Calculate the average charge amount of each of the plurality of battery cells based on the SOC after the above charging, Calculate the degree of change in the charge amount compared to the average according to the charging cycle of each of the above plurality of battery cells, An index value is calculated by applying a cycle-by-cycle weight to the degree of change in the charge amount of the battery cell to be diagnosed compared to the average among the plurality of battery cells, A battery diagnostic device comprising one or more processors that diagnose an abnormality in a battery cell to be diagnosed based on cycle-by-cycle indicator values ​​of the battery cell to be diagnosed.

2. In paragraph 1, The above interface part, A battery diagnostic device that obtains, for each of the plurality of battery cells, the SOC after a specified time has elapsed after each charging cycle has ended.

3. In paragraph 1, The above processor, The average SOC of each of the above plurality of battery cells is calculated for each charging cycle, The overall cycle average is calculated based on the average SOCs calculated after each charging cycle, and A battery diagnostic device that calculates the amount of charge compared to the average based on the SOC after the charging, the average SOC after the charging, and the average of the entire cycle.

4. In paragraph 1, The above processor, A battery diagnostic device that calculates a difference value between the average charge amount in a first charging cycle among multiple charging cycles and the average charge amount in a second charging cycle prior to the first charging cycle as a degree of change in the average charge amount corresponding to the first charging cycle.

5. In paragraph 1, The above processor, Calculate the average change degree representing the average of the change degrees of the charge amount compared to the average in the first charging cycle of the remaining battery cells other than the battery cell to be diagnosed among the plurality of battery cells, and Identifying the minimum change degree representing the minimum value among the changes in the charge amount compared to the average in the first charging cycle of the remaining battery cells, A battery diagnosis device that calculates a weight in the first charging cycle by multiplying a larger value between the average change degree and the minimum change degree and the change degree of the amount of charge compared to the average in the first charging cycle of the battery cell to be diagnosed.

6. In paragraph 5, The above processor, A battery diagnostic device that divides the change in the charge amount compared to the average in the first charging cycle of the battery cell to be diagnosed by a weight in the first charging cycle to calculate an index value corresponding to the first charging cycle.

7. In paragraph 1, The above processor, A battery diagnostic device that diagnoses an abnormality in a battery cell to be diagnosed by comparing the maximum value and the threshold value among the cycle-by-cycle indicator values ​​of the battery cell to be diagnosed.

8. For each of the plurality of battery cells, a step of obtaining the SOC after charging for each charging cycle; A step of calculating the average charge amount of each of the plurality of battery cells based on the SOC after the charging; A step of calculating the degree of change in the amount of charge compared to the average according to the charging cycle of each of the plurality of battery cells; A step of calculating an index value by applying a cycle-by-cycle weight to the degree of change in the charge amount of a battery cell to be diagnosed compared to the average among the plurality of battery cells; and A battery diagnosis method, comprising a step of diagnosing an abnormality in a battery cell to be diagnosed based on cycle-by-cycle indicator values ​​of the battery cell to be diagnosed.

9. In paragraph 8, The step of obtaining SOC after the above charging is: A battery diagnosis method characterized in that, for each of the plurality of battery cells, an SOC is obtained after a specified time has elapsed after each charging cycle is completed.

10. In paragraph 8, The step of calculating the average charge amount of each of the plurality of battery cells is as follows: A step of calculating an average SOC for each charging cycle after charging each of the plurality of battery cells; A step of calculating an overall cycle average based on the calculated post-charge average SOCs for each charging cycle; and A battery diagnosis method, comprising a step of calculating a charge amount relative to the average based on the SOC after charging, the average SOC after charging, and the average of the entire cycle.

11. In paragraph 8, The step of calculating the degree of change in the charge amount compared to the above average is: A battery diagnosis method characterized in that the difference value between the average charge amount in a first charging cycle among multiple charging cycles and the average charge amount in a second charging cycle prior to the first charging cycle is calculated as the degree of change in the average charge amount corresponding to the first charging cycle.

12. In paragraph 8, The step of calculating the above indicator value is: A step of calculating an average change degree representing the average of the change degrees of the charge amount compared to the average in the first charging cycle of the remaining battery cells other than the battery cell to be diagnosed among the plurality of battery cells; A step of identifying a minimum change degree representing a minimum value among the changes in the charge amount compared to the average in the first charging cycle of the remaining battery cells; A step of calculating a weight in the first charging cycle by multiplying a larger value between the average change degree and the minimum change degree and the change degree of the amount of charge compared to the average in the first charging cycle of the battery cell to be diagnosed; and A battery diagnosis method, comprising a step of dividing the degree of change in the charge amount compared to the average in the first charging cycle of the battery cell to be diagnosed by a weight in the first charging cycle to calculate an index value corresponding to the first charging cycle.

13. In paragraph 8, The steps for diagnosing the abnormality of the above diagnostic battery cell are: A battery diagnosis method characterized in that an abnormality in the battery cell to be diagnosed is diagnosed by comparing the maximum value and the threshold value among the cycle-by-cycle indicator values ​​of the battery cell to be diagnosed.

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