Battery diagnostic device and its operating method

Abstract

The battery diagnostic device according to the embodiment disclosed in this document may include: a voltage acquisition unit that acquires voltage information for each of a plurality of battery units contained in each of a plurality of vehicles; and a controller that calculates the cumulative voltage change amount for each of the plurality of battery units based on the voltage information, calculates at least one deviation value which is the deviation between the cumulative voltage change amounts for each of the plurality of vehicles, and manages the plurality of battery units based on the distribution of the at least one deviation value for the plurality of vehicles.

Description

Technical Field

[0001] The present invention claims the benefit of priority based on Korean Patent Application No. 10-2023-0125303 filed on September 20, 2023, and all the contents disclosed in the document of the Korean patent application are incorporated herein by reference in their entirety. The embodiments disclosed in this document relate to a battery diagnostic apparatus and an operating method thereof.

Background Art

[0002] In recent years, research and development on secondary batteries have been actively conducted. Here, a secondary battery is a battery that can be charged and discharged, and can be interpreted to include all conventional Ni / Cd batteries, Ni / MH batteries, etc., and recent lithium-ion batteries. In recent years, its range of use has expanded to the power source of electric vehicles and has attracted attention as a next-generation energy storage medium.

[0003] An electric vehicle receives electrical supply from the outside to charge a battery cell, and then discharges the battery cell to drive a motor to obtain power. The battery cell undergoes internal deformation and denaturation due to various charge and discharges during production and use, and its physicochemical properties change. For example, internal short circuit, external short circuit, venting due to lithium precipitation, or under voltage failure where the voltage of the battery cell decreases below a certain level may occur. Due to such aging and deterioration of the battery, a technology for diagnosing and managing the state of the battery cell is required.

Summary of the Invention

Problems to be Solved by the Invention

[0004] One object of the embodiments disclosed in this document is to provide a battery diagnostic apparatus and an operating method thereof that can diagnose abnormal battery cells based on the amount of voltage change in a battery bank.

[0005] One objective of the embodiments disclosed in this document is to provide a battery diagnostic device and a method for operating the same that can diagnose the type of abnormality of an abnormal battery cell based on the cumulative voltage change of a battery bank.

[0006] The technical problems of the embodiments disclosed in this document are not limited to those mentioned above, and other technical problems not mentioned can be clearly understood by those skilled in the art from the following description. [Means for solving the problem]

[0007] The battery diagnostic device according to the embodiment disclosed in this document may include: a voltage acquisition unit that acquires voltage information for each of a plurality of battery units contained in each of a plurality of vehicles; and a controller that calculates the cumulative voltage change amount for each of the plurality of battery units based on the voltage information, calculates at least one deviation value which is the deviation between the cumulative voltage change amounts for each of the plurality of vehicles, and manages the plurality of battery units based on the distribution of the at least one deviation value for the plurality of vehicles.

[0008] According to the embodiment, each of the plurality of vehicles may have at least one of the first and second standard scores. According to the embodiment, the controller can calculate the first deviation value by dividing the difference between the maximum and median values ​​of the cumulative voltage change of each of the multiple battery units included in each of the multiple vehicles by the standard deviation of the cumulative voltage change of each of the multiple battery units.

[0009] According to the embodiment, the controller can calculate the second deviation value by dividing the difference between the minimum and median values ​​of the cumulative voltage change of each of the multiple battery units included in each of the multiple vehicles by the standard deviation of the cumulative voltage change of each of the multiple battery units.

[0010] According to the embodiment, the controller can calculate a first distribution of the plurality of vehicles based on the first deviation score and calculate a second distribution of the plurality of vehicles based on the second deviation score.

[0011] According to the embodiment, the controller can diagnose a vehicle in the distribution of at least one deviation value of the plurality of vehicles in which the deviation value is greater than or equal to a threshold as an abnormal vehicle containing an abnormal battery unit.

[0012] According to the embodiment, the controller can diagnose that the battery unit with the largest cumulative voltage change among the multiple battery units included in the abnormal vehicle is in a capacity abnormal state.

[0013] According to the embodiment, the controller can diagnose an insulation abnormality in one of the multiple battery units included in the abnormal vehicle, specifically the one with the smallest cumulative voltage change. According to one embodiment, the voltage information may be the voltages acquired during the charging intervals of the plurality of battery units.

[0014] A battery diagnostic method according to one embodiment disclosed herein may include the steps of: acquiring voltage information for each of a plurality of battery units contained in each of a plurality of vehicles; calculating the cumulative voltage change amount for each of the plurality of battery units based on the voltage information; calculating at least one deviation value which is the deviation between the cumulative voltage change amounts for each of the plurality of vehicles; and managing the plurality of battery units based on the distribution of the at least one deviation value for the plurality of vehicles.

[0015] According to the embodiment, each of the plurality of vehicles may have at least one of the first and second standard scores. According to the embodiment, the step of calculating the at least one deviation value may include the step of calculating the first deviation value by dividing the difference between the maximum and median values ​​of the cumulative voltage change of each of the plurality of battery units contained in each of the plurality of vehicles by the standard deviation of the cumulative voltage change of each of the plurality of battery units.

[0016] According to one embodiment, the step of calculating the at least one deviation value may include the step of calculating the second deviation value by dividing the difference between the minimum and median values ​​of the cumulative voltage change of each of the plurality of battery units contained in each of the plurality of vehicles by the standard deviation of the cumulative voltage change of each of the plurality of battery units.

[0017] According to the embodiment, the method may further include the steps of calculating a first distribution of the plurality of vehicles based on the first standard score and calculating a second distribution of the plurality of vehicles based on the second standard score.

[0018] According to one embodiment, the step of managing the plurality of battery units may include the step of diagnosing a vehicle in which the deviation value of at least one of the distributions of deviation values ​​of the plurality of vehicles is greater than or equal to a threshold as an abnormal vehicle containing an abnormal battery unit.

[0019] According to one embodiment, the process may further include the step of diagnosing a capacity abnormality state in which, among a plurality of battery units included in the abnormal vehicle, the battery unit with the largest cumulative voltage change is in a capacity abnormal state.

[0020] According to one embodiment, the further step may include diagnosing a battery unit with the smallest cumulative voltage change among a plurality of battery units included in the abnormal vehicle as being in an insulation abnormal state. According to one embodiment, the voltage information may be the voltages acquired during the charging intervals of the plurality of battery units. [Effects of the Invention]

[0021] The battery diagnostic device and its operating method according to the embodiments disclosed herein can diagnose abnormal battery cells based on the voltage change of the battery bank.

[0022] The battery diagnostic device and its operating method according to the embodiments disclosed herein can diagnose the type of abnormality of an abnormal battery cell based on the cumulative voltage change of the battery bank. In addition, this document can provide various effects that can be understood directly or indirectly. [Brief explanation of the drawing]

[0023] [Figure 1] This figure shows a battery diagnostic system according to one embodiment disclosed in this document. [Figure 2] This figure shows a battery pack according to one embodiment disclosed in this document. [Figure 3] This is a block diagram showing the configuration of a battery diagnostic device according to one embodiment disclosed in this document. [Figure 4] This is a graph showing the voltage of a battery unit according to one embodiment disclosed in this document. [Figure 5] This figure shows the distribution of standard scores according to one embodiment disclosed in this document. [Figure 6] This is a flowchart showing the operation of a battery diagnostic device according to one embodiment disclosed in this document. [Figure 7] This is a flowchart showing the operation of a controller according to one embodiment disclosed in this document. [Figure 8] This is a block diagram showing the hardware configuration of a computing system that implements the operation method of a battery management device according to one embodiment disclosed in this document. [Modes for carrying out the invention]

[0024] Various embodiments of the present invention are described below with reference to the accompanying drawings. However, this should be understood not as limiting the present invention to any particular embodiment, but rather as including various modifications, equivalents, and / or alternatives to the embodiments of the present invention.

[0025] The various embodiments and terminology used in this document are not intended to limit the technical features described herein to any particular embodiment, but should be understood to include various modifications, equivalents, or substitutes of such embodiments. In relation to the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more such items unless the context clearly indicates otherwise.

[0026] In this document, each phrase such as “A or B,” “at least one of A and B,” “at least one of A or B,” “A, B, or C,” “at least one of A, B, and C,” and “at least one of A, B, or C” may include any one of the items listed together with the applicable phrase, or any possible combination thereof. Terms such as “first,” “second,” “first,” “second,” “A,” “B,” “(a),” or “(b)” may be used simply to distinguish one component from other components and, unless otherwise stated, do not limit the component in any other respect (e.g., importance or order).

[0027] Wherever a component (e.g., the first) is referred to as being "coupled," "joined," or "connected" to another component (e.g., the second) with or without such terms, it means that the first component may be connected to the other component directly (e.g., by wire), wirelessly, or via the third component.

[0028] According to one embodiment, the methods according to the various embodiments disclosed herein may be provided in a computer program product. The computer program product may be traded as a commodity between a seller and a buyer. The computer program product may be distributed in the form of an instrument-readable storage medium (e.g., compact disc read-only memory (CD-ROM)) or online (e.g., download or upload) via an application store or directly between two user devices. In the case of online distribution, at least a portion of the computer program product may be at least temporarily stored or temporarily generated in an instrument-readable storage medium such as the memory of a manufacturer's server, an application store server, or an intermediary server.

[0029] According to various embodiments, each of the aforementioned components (e.g., a module or a program) may include one or more individuals, and some of the individuals may be separated and arranged in other components. According to various embodiments, one or more of the aforementioned components or operations may be omitted, or one or more other components or operations may be added. Alternatively or additionally, multiple components (e.g., a module or a program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the components of the multiple components before the integration. According to various embodiments, 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.

[0030] Figure 1 shows a battery diagnostic system according to one embodiment disclosed in this document. Figure 2 shows a battery pack according to one embodiment disclosed in this document.

[0031] Referring to Figure 1, the battery diagnostic system 1 according to various embodiments may include a plurality of vehicles 10 and 20, battery packs 1000 and 2000 contained in each of the plurality of vehicles 10 and 20, and a battery diagnostic device 3000.

[0032] According to the embodiment, each of the multiple vehicles 10 and 20 may include an electrically powered, electronic, or mechanical vehicle that operates by receiving power from the battery packs 1000 and 2000, respectively. For example, the multiple vehicles 10 and 20 may include electric vehicles (EVs) and / or electric motorcycles. On the other hand, although Figure 1 shows the multiple vehicles 10 and 20 as consisting of two vehicles, the multiple vehicles 10 and 20 can be configured to include n vehicles (where n is a natural number greater than or equal to 2).

[0033] According to the embodiment, the multiple vehicles 10 and 20 can consist of vehicles of the same type. For example, the multiple vehicles 10 and 20 may be models with the same specifications produced by the same EV manufacturer. If the multiple vehicles 10 and 20 are vehicles of the same type, the specifications of the components included in each of the multiple vehicles 10 and 20 (e.g., battery packs 1000 and 2000, sensors, motors, accelerators, and deceleration devices) will be similar, and the specifications of the multiple vehicles 10 and 20 (e.g., charge / discharge mechanisms and energy consumption) will be similar. Therefore, the battery diagnostic device 3000 can obtain consistent information from the multiple vehicles 10 and 20, and can improve the accuracy of battery diagnostics based on the obtained information.

[0034] The battery packs 1000 and 2000 are installed inside vehicles 10 and 20 and can acquire battery-related information regarding the charging / discharging state or driving state of vehicles 10 and 20. Battery-related information may include battery voltage information during charging or discharging intervals of vehicles 10 and 20, and battery voltage information during driving states of vehicles 10 and 20. A detailed description of the battery packs 1000 and 2000 will be provided with reference to Figure 2 below.

[0035] Referring to Figure 2, the battery pack 1000 may include a higher-level battery unit 100 and a battery management device 200. The battery pack 1000 may be contained inside the vehicle 10. For convenience of explanation, Figure 2 shows the battery pack 1000 contained in the vehicle 10, but the following description of the battery pack 1000 can also be applied to the battery pack 2000 contained in the vehicle 20.

[0036] The upper battery unit 100 may include a plurality of battery units 110, 120, ..., 130. For example, if the upper battery unit 100 is a battery module, the plurality of battery units 110, 120, ..., 130 may be a plurality of battery cells. For example, the plurality of battery units 110, 120, ..., 130 may be, but are not limited to, lithium-ion (Li-ion) batteries, lithium-ion polymer (Li-ion polymer) batteries, nickel-cadmium (Ni-Cd) batteries, nickel-metal hydride (Ni-MH) batteries, etc.

[0037] According to the embodiment, if the upper battery unit 100 is a battery module, the multiple battery units 110, 120, ..., 130 may be multiple battery banks. A battery bank may be a collection of multiple battery cells. For example, a battery bank may be a collection of battery cells containing three battery cells. According to the embodiment, the battery pack 1000 may include 98 battery banks.

[0038] On the other hand, although Figure 1 shows that there is one upper battery unit 100, the battery pack 1000 is not limited to this, and can be composed of n (where n is a natural number greater than or equal to 2) upper battery units. Furthermore, some components may be omitted from the battery pack 1000, and other general-purpose components may be further included in the battery pack 1000.

[0039] The higher-level battery unit 100 can supply power to the target device (e.g., a vehicle 10 or 20). For this purpose, the higher-level battery unit 100 can be electrically connected to the target device. Here, the target device may include electrical, electronic, or mechanical devices that operate on power supplied from the battery pack 1000, which includes the higher-level battery unit 100. For example, the target device may be, but is not limited to, an electric vehicle (EV) or an energy storage system (ESS).

[0040] The battery management device 200 can manage and / or control the state and / or operation of the upper battery unit 100 and / or each of the multiple battery units 110, 120, ..., 130.

[0041] For the convenience of describing the operation of the battery management device 200, the higher-level battery unit 100 and / or the multiple battery units 110, 120, ..., 130 will each be referred to as battery unit 110, but this can be applied substantially similarly to the other battery units 120, ..., 130 or the higher-level battery unit 100.

[0042] According to the embodiment, the battery management device 200 can determine the state of the battery unit 110 and manage the state of the battery unit 110 based on that determination. According to the embodiment, the battery management device 200 can control the operation of the battery unit 110 and manage the operation of the battery unit 110 based on that control.

[0043] According to the embodiment, the battery management device 200 can monitor the voltage, current, and / or temperature of the battery unit 110. For monitoring purposes, sensors and various measuring modules (not shown) can be further provided at any location on the upper battery unit 100, the charge / discharge path, or on multiple battery units 110, 120, ..., 130.

[0044] According to the embodiment, the battery management device 200 can calculate battery information regarding the state of the battery unit 110 based on measured values ​​such as monitored voltage, current, and temperature. For example, the battery information regarding the state of the battery unit 110 may include at least one of the following: SOC (State of Charge), SOH (State of Health), resistance, current cycle, remaining predicted cycle, and C-rate.

[0045] According to one embodiment, the battery management device 200 may include an OBD (On-Board Diagnostic) device. Such an OBD device may include not only OBD-I, OBD 1.5, and OBD-II, but also various devices that output information related to the status of the battery unit 110 to other devices (e.g., a battery diagnostic device 3000). Furthermore, the operation of the battery management device 200 can be performed by various devices such as a server, cloud, charger, or charger / discharger connected to a BMS (Battery Management System) or a vehicle equipped with the battery management device 200.

[0046] According to this embodiment, the battery management device 200 can transmit monitored voltage, current, and temperature information, as well as calculated battery information, to the battery diagnostic device 3000 (see Figure 1). The voltage, current, temperature, and battery information may include information about the battery unit 110 from which each piece of information was monitored or calculated. For example, the battery information may include a unique identification number for the battery unit 110.

[0047] Referring again to Figure 1, the battery diagnostic device 3000 can receive various information acquired via the battery management device 200 and manage the status of the battery unit 110 based on the received information. For example, the battery diagnostic device 3000 can diagnose abnormal battery units inside the battery packs 1000 and 2000 contained in each of the multiple vehicles 10 and 20.

[0048] According to various embodiments, abnormalities in battery cells can occur due to a variety of causes, such as defects during the production stage of the battery cell, internal deformation and modification due to charging and discharging, or external impact. These abnormalities in the battery cell may include lithium deposition, wire breakage, or short circuits.

[0049] According to the embodiment, the abnormal state of the battery cell can include two types: capacity abnormality and insulation abnormality. For example, a capacity abnormality may arise from lithium deposition in the battery cell, and an insulation abnormality may arise from an internal short circuit in the battery cell. According to the embodiment, an insulation abnormality may include a short circuit between electrodes inside the battery cell or damage to the separator inside the battery cell. Here, when an abnormality occurs in the battery cell, the resistance of the battery cell will exhibit a different appearance compared to a normal battery cell, and therefore the voltage change of the abnormal battery cell may exhibit a different appearance compared to the voltage change of a normal battery cell.

[0050] According to the embodiment, the battery diagnostic device 3000 can diagnose abnormal battery units based on voltage information of multiple battery units 110, 120, ..., 130 acquired in the charge-discharge section. For example, the battery diagnostic device 3000 can diagnose battery unit 110 as having a capacity abnormality if the voltage of battery unit (e.g., 110) in the charge-discharge section changes faster and more significantly than the voltage of a normal battery unit (e.g., 120, ..., 130). Also, the battery diagnostic device 3000 can diagnose battery unit 130 as having an insulation abnormality if the voltage of battery unit (e.g., 130) in the charge-discharge section changes slower and less significantly than the voltage of a normal battery unit (e.g., 110, ..., 120).

[0051] The operation of the battery diagnostic device 3000 can be performed by various devices such as a battery management device 200, a BMS (Battery Management System), or a server, cloud, charger, or charger / discharger connected to a vehicle equipped with a battery management device. The details related to the abnormal diagnosis of the battery unit 110 performed by the battery diagnostic device 3000 according to this embodiment will be described in detail with reference to the following drawings.

[0052] Figure 3 is a block diagram showing the configuration of a battery diagnostic device according to one embodiment disclosed in this document. Referring to Figure 3, the battery diagnostic device 3000 may include a voltage acquisition unit 310 and a controller 320. However, it is not limited to this, and some components may be omitted from the battery diagnostic device 3000, and other general-purpose components may be further included in the battery diagnostic device 3000.

[0053] The voltage acquisition unit 310 can acquire voltage information of batteries contained in each of the multiple vehicles 10 and 20. According to the embodiment, the voltage acquisition unit 310 can acquire voltage information of each of the multiple battery units 110, 120, ..., 130 contained in each of the multiple vehicles 10 and 20.

[0054] The voltage acquisition unit 310 can acquire voltage information for each of the multiple battery units 110, 120, ..., 130 measured during a predetermined time interval, on a unit time basis. According to the embodiment, the voltage acquisition unit 310 can continuously acquire information related to the rise and fall of voltage during the charging interval, the rest interval after charging, the discharge interval, and / or the rest interval after discharge of the multiple battery units 110, 120, ..., 130.

[0055] According to the embodiment, the voltage acquisition unit 310 can acquire voltage information in the charging section of multiple vehicles 10 and 20 during a predetermined period. For example, the predetermined period may include a set period such as one week, two weeks, or one month. The predetermined period may also be determined based on a predetermined number of charge-discharge cycles. For example, the voltage information of multiple battery units 110, 120, ..., 130 acquired by the voltage acquisition unit 310 may include charging voltage information for which the number of charge cycles is at least five or more. If the number of charge cycles is small, the population voltage information for diagnosing the multiple battery units 110, 120, ..., 130 is insufficient. Therefore, by acquiring voltage information in the charging section during a predetermined period, the voltage acquisition unit 310 can improve the reliability of diagnosing abnormal battery units. According to the embodiment, the voltage acquisition unit 310 may include a voltage monitoring circuit or sensor.

[0056] The controller 320 can control the operation of the battery diagnostic device 3000. The controller 320 can also manage the status of the upper-level battery unit 100 and the multiple battery units 110, 120, ..., 130. According to the embodiment, the controller 320 can determine whether each of the multiple battery units 110, 120, ..., 130 is abnormal and manage its status based on the voltages of the multiple battery units 110, 120, ..., 130 acquired by the voltage acquisition unit 310.

[0057] According to one embodiment, the controller 320 can diagnose an abnormal battery unit based on voltage information in the charge-discharge intervals of a plurality of battery units 110, 120, ..., 130. According to another embodiment, the controller 320 can diagnose a vehicle 10 containing an abnormal battery unit (e.g., 110) as an abnormal vehicle.

[0058] According to the embodiment, the controller 320 can diagnose the type of abnormal state of the battery unit 110. For example, the controller 320 can diagnose whether an abnormal battery unit (e.g., 110) is in a capacity abnormal state or an insulation abnormal state. Depending on the type of abnormal state of the battery unit 110, the voltage of the higher-level battery unit 100 may exhibit different behavior. Therefore, the controller 320 can analyze the trend of abnormal values ​​based on the voltage information of multiple battery units 110, 120, ..., 130 contained in each of the multiple vehicles 10 and 20, and diagnose the type of abnormal state of each of the multiple battery units 110, 120, ..., 130.

[0059] The controller 320 may have a structure for executing instructions that enable the operation of the battery diagnostic device 3000. The controller 320 can be implemented as an array of multiple logic gates or a general-purpose microprocessor for processing various operations, and can consist of a single processor or multiple processors. For example, the controller 320 can be implemented in the form of at least one of the following: a microprocessor, a CPU, a GPU, and an AP.

[0060] The controller 320 can be configured separately from or integrated with memory and / or storage configured to temporarily store data or instruction words, and can execute instruction words stored in memory and / or storage to process various operations. Memory and / or storage can store various data, instruction words, mobile applications, computer programs, etc. For example, memory and / or storage can be implemented as non-volatile devices such as ROM, PROM, EPROM, EEPROM, flash memory, PRAM, MRAM, RRAM®, FRAM®, or volatile devices such as DRAM, SRAM, SDRAM, PRAM, RRAM, FeRAM, and can be implemented in the form of HDD, SSD, SD, Micro-SD, or a combination thereof.

[0061] The controller 320 manages each of the multiple battery units 110, 120, ..., 130 by analyzing voltage information during the charging / discharging and / or resting periods, and can diagnose the status of each of the multiple battery units 110, 120, ..., 130. If the diagnosis confirms that there is an abnormality in a battery unit (e.g., 110), the controller 320 can provide information about the abnormal battery unit (e.g., 110) to the user. For example, the controller 320 can provide information about the abnormal battery unit to a user terminal via a communication circuit (not shown), as well as via a display provided in the vehicle or charger. The detailed operation of the controller 320 according to this embodiment will be explained with reference to Figure 4 below.

[0062] Figure 4 is a graph showing the voltage of a battery unit according to one embodiment disclosed in this document. Referring to Figure 4, the controller 320 can acquire time-series information of the voltage of each of the multiple battery units 110, 120, ..., 130 based on the voltage information of the multiple battery units 110, 120, ..., 130 acquired by the voltage acquisition unit 310 at unit time intervals. According to the embodiment, the voltage information of the multiple battery units 110, 120, ..., 130 can be acquired in predetermined time intervals. For example, the voltage information may be the voltage acquired in the charging interval of each of the multiple battery units 110, 120, ..., 130.

[0063] The controller 320 can calculate a graph (e.g., a voltage graph) showing the voltage change of each of the multiple battery units 110, 120, ..., 130 based on the voltage information of each of the multiple battery units 110, 120, ..., 130 for each unit of time. According to the embodiment, the voltage graph may be a graph relating the voltage of each of the multiple battery units 110, 120, ..., 130 to time. For example, the x-axis of the voltage graph may be time (unit: hours) and the y-axis may be voltage (unit: volts).

[0064] The controller 320 can calculate the voltage profile of the first battery unit (A) and the voltage profile of the second battery unit (B) as voltage graphs. Although only two battery units are shown in Figure 4, the controller 320 can calculate voltage graphs based on the voltage information of multiple battery units 110, 120, ..., 130 contained in battery packs 1000 and 2000 contained in multiple vehicles 10 and 20, respectively.

[0065] According to the embodiment, the controller 320 can calculate a voltage graph based on voltage information acquired in the charging intervals of each of the multiple battery units 110, 120, ..., 130. For example, T1 to T2 may represent the first charging intervals (T1 to T2) in which the first battery unit (A) and the second battery unit (B) are charged.

[0066] Voltage information for multiple battery units 110, 120, ..., 130 during a charging section can include information about the voltage increase when a constant current is applied. In contrast, voltage information during a driving section or discharge section can include voltage increase and voltage decrease regions. Therefore, voltage information during a driving section or discharge section cannot show the relationship between the applied current and voltage, and cannot accurately represent the state of the multiple battery units 110, 120, ..., 130. In another embodiment, voltage information during a charging section can more accurately represent the state of the multiple battery units 110, 120, ..., 130 than voltage information during a driving section, discharge section, or rest section. Therefore, the controller 320 can more accurately manage the behavior of the multiple battery units 110, 120, ..., 130 than data acquired during a driving section, discharge section, or rest section by using the voltage acquired during the charging section of each of the multiple battery units 110, 120, ..., 130.

[0067] According to the embodiment, the controller 320 controls the voltage change (V) in the charging interval of each of the multiple battery units 110, 120, ..., 130. △) can be calculated. Here, the voltage change amount (V △ ) may mean the degree to which the voltages of the plurality of battery units 110, 120,..., 130 increase in one charging interval. In other embodiments, the voltage change amount (V △ ) in the charging interval of each of the plurality of battery units 110, 120,..., 130 may mean the difference between the charging end voltage (V2) and the charging start voltage (V1) of the charging interval. According to an embodiment, the controller 320 can calculate the voltage change amount (V △ ) of each of the plurality of battery units 110, 120,..., 130 in the charging interval according to the following <Equation 1>.

[0068] <Equation 1> V △1 (k) = V2(k) - V1(k)

[0069] In <Equation 1>, k represents an arbitrary k-th battery unit (k), V △1 (k) represents the voltage change amount of the battery unit (k) in the first charging interval, V1(k) represents the charging start voltage of the first charging interval of the battery unit (k), and V2(k) may represent the charging end voltage of the first charging interval of the battery unit (k). For example, the voltage change amount (V △1 (A)) of the first battery unit (A) in the first charging interval (T1 to T2) may mean the difference between the charging end voltage (V2(A)) and the charging start voltage (V1(A)) of the first charging interval (V △1 (A) = V2(A) - V1(A)).

[0070] According to an embodiment, the controller 320 can calculate the cumulative voltage change amount (V △ ) of each of the plurality of battery units 110, 120,..., 130 based on the voltage change amount (V △tot ) of each of the plurality of battery units 110, 120,..., 130. Here, the cumulative voltage change amount (V △tot (k)) of the k-th battery unit (k) is the voltage change amount (V △1 (k), V △2 (k),..., V△3 (k)) may mean the sum of the values ​​of each of the multiple battery units 110, 120, ..., 130. △tot ) is the first voltage change (V) obtained in the first charging section, second charging section, ..., third charging section, respectively. △1 ), second voltage change (V △2 ), ..., Third voltage change (V △3 ) may include the cumulative value. According to the embodiment, the controller 320 may include the cumulative voltage change (V) based on the voltage information of each of the multiple battery units 110, 120, ..., 130 acquired over five or more charging intervals. △tot ) can be calculated.

[0071] According to the embodiment, the controller 320 calculates the cumulative voltage change (V) of each of the multiple battery units 110, 120, ..., 130 in the charging section using the following <Equation 2>. △tot It is possible to calculate ).

[0072] <Expression 2> V △tot (k=V △1 (k) + V △2 (k) + ... + V △3 (k)

[0073] In <Equation 2>, k represents the kth battery unit (k), V △tot (k) is the cumulative voltage change of the battery unit (k) in multiple charging intervals, V △1 (k) is the amount of voltage change of the battery unit (k) in the first charging section, V △2 (k) is the change in voltage of the battery unit (k) during the second charging section, V △3 (k) may represent the change in voltage of battery unit (k) during the third charging interval. For example, the cumulative change in voltage (V) of the first battery unit (A) during the fifth charging interval. △tot (A)) is the voltage change (V) in the first charging section. △1 (A)) Voltage change in the second charging section (V △2 (A)) Voltage change in the third charging section (V △3(A)) Voltage change in the fourth charging section (V △4 (A)), and the amount of voltage change (V) in the fifth charging section. △5 (A)) Can mean total (V △tot (A) = V △1 (A) + V △2 (A) + V △3 (A) + V △4 (A) + V △5 (A)).

[0074] According to the embodiment, the amount of voltage change (V) of the first battery unit (A) in the first charging section △1 (A)) and the voltage change (V) of the second battery unit (B) △1 (B)) difference (V △1 (A)-V △1 (B)) is very small. In contrast, the cumulative voltage change (V) of the first battery unit (A) calculated over multiple charging intervals △tot (A)) and the cumulative voltage change (V) of the second battery unit (B) △tot (B)) difference (V △tot (A)-V △tot (B)) is the difference in the amount of voltage change (V △1 (A)-V △1 (B)) can have a larger value. Therefore, the controller 320 can determine the cumulative voltage change (V) of each of the multiple battery units 110, 120, ..., 130 in multiple charging intervals. △tot Based on (k), the voltage change can be analyzed more reliably, and abnormal battery units can be accurately diagnosed.

[0075] According to the embodiment, the amount of voltage change (V) over time for each of the multiple battery units 110, 120, ..., 130 is △ ) or cumulative voltage change (V △totThe slope of the ) can include resistance information. Factors that affect the resistance of a battery cell include battery cell defects such as lithium deposition, open circuits, or short circuits. For example, abnormal conditions of a battery cell can include two types: capacity abnormality and insulation abnormality. A capacity abnormality can result from lithium deposition in the battery cell, and an insulation abnormality can result from an internal short circuit in the battery cell. According to the embodiment, an insulation abnormality can include a short circuit between electrodes inside the battery cell or damage to the separator inside the battery cell. When an abnormality occurs in a battery cell, the resistance of the battery cell will show a different appearance compared to a normal battery cell, and therefore the voltage change of an abnormal battery cell can show a different appearance compared to the voltage change of a normal battery cell. Accordingly, the controller 320 calculates the cumulative voltage change (V) of each of the multiple battery units 110, 120, ..., 130 over multiple time intervals. △tot The controller 320 calculates the cumulative voltage change (V) of each of the battery units 110, 120, ..., 130 and manages them based on the calculated cumulative voltage change. △tot This section describes the process of calculating the standard deviation (D) among multiple battery units 110, 120, ..., 130 based on the above, and then calculating the distribution (P) of the standard deviations.

[0076] Figure 5 shows the distribution of standard scores according to one embodiment disclosed in this document. Referring to Figure 5, the controller 320 calculates the cumulative voltage change (V) for each of the multiple vehicles 10 and 20. △tot (A), V △tot (B), ..., V △tot The deviation score (D), which is the deviation between (k), can be calculated. Here, the deviation score (D) is the cumulative voltage change (V) of multiple battery units 110, 120, ..., 130 contained in a single vehicle 10. △tot (A), V △tot (B), ..., V △tot(k)) may represent the degree to which it deviates from the median. According to the embodiment, the controller 320 can calculate a deviation value (D) for each single vehicle 10 or 20. This allows the controller 320 to detect abnormal values ​​among a plurality of battery units 110, 120, ..., 130 contained in a single vehicle 10 or 20.

[0077] According to the embodiment, the controller 320 can calculate at least one standard score (D) for each of the multiple vehicles 10 and 20. Here, at least one standard score (D) may include a first standard score (D1) and a second standard score (D2). For example, the controller 320 can calculate the first standard score (D1) and the second standard score (D2) for vehicle 10, and can calculate the first standard score (D1) and the second standard score (D2) for vehicle 20.

[0078] The following describes how the controller 320 calculates the deviation value between cumulative voltage changes based on vehicle 10, but it is not limited to this, and the same method can be applied to how the controller 320 calculates the deviation value of vehicle 20.

[0079] According to the embodiment, the controller 320 can calculate a first deviation value (D1) of the vehicle 10 based on the cumulative voltage change of the battery unit having the largest cumulative voltage change among the multiple battery units 110, 120, ..., 130 included in the vehicle 10. The controller 320 can also calculate a second deviation value (D2) of the vehicle 10 based on the cumulative voltage change of the battery unit having the smallest cumulative voltage change among the multiple battery units 110, 120, ..., 130 included in the vehicle 10. As a result, the controller 320 can diagnose which of the multiple battery units 110, 120, ..., 130 included in the vehicle 10 has the largest or smallest cumulative voltage change based on at least one of the first deviation value (D1) and the second deviation value (D2).

[0080] According to the embodiment, the controller 320 controls the cumulative voltage change (V) of each of the multiple battery units 110, 120, ..., 130 included in the vehicle 10. △tot The difference between the maximum and median values ​​of the multiple battery units 110, 120, ..., 130 is the cumulative voltage change (V) △tot The first deviation value (D1) can be calculated by dividing by the standard deviation of ). According to the embodiment, the controller 320 calculates the cumulative voltage change (V) of each of the multiple battery units 110, 120, ..., 130 included in the vehicle 10. △tot The difference between the minimum and median values ​​of ) is the cumulative voltage change (V) of each of the multiple battery units 110, 120, ..., 130. △tot The second standard deviation (D2) can be calculated by dividing by the standard deviation of the first standard deviation (D1). Therefore, the controller 320 can detect abnormal values ​​based on the first standard deviation (D1) and the second standard deviation (D2) and diagnose abnormal battery units among the multiple battery units 110, 120, ..., 130.

[0081] According to the embodiment, the controller 320 can calculate the first standard score (D1) based on <Equation 3> and the second standard score (D2) based on <Equation 4>.

[0082] <Expression 3> D1=(V △tot (Max)-V △tot (Med)) / (Std(V △tot )) <Expression 4> D2=(V △tot (Med)-V △tot (Min)) / (Std(V △tot ))

[0083] In <Equation 3> and <Equation 4>, D1 is the first standard score, D2 is the second standard score, and V △tot (Max) is the maximum value of the cumulative voltage change, V △tot (Min) is the minimum value of the cumulative voltage change, V △tot (Med) is the median of the cumulative voltage change, and Std(V △tot) may mean the standard deviation of the cumulative voltage change. Here, the controller 320 calculates the first deviation value (D1) and the second deviation value (D2) based on a single vehicle (e.g., 10), and calculates the maximum value (V) of the cumulative voltage change based on the cumulative voltage change of multiple battery units 110, 120, ..., 130 contained in a single vehicle (e.g., 10). △tot (Max), Minimum value of cumulative voltage change (V △tot (Min)), median value of cumulative voltage change (V △tot (Med)), and the standard deviation of the cumulative voltage change (Std(V △tot All of the following can be calculated.

[0084] The cumulative voltage change (V) of most battery units △tot ) is the median (V) for all battery units. △tot While not showing a significant difference from (Med), the voltage change of some defective battery units may show a large deviation. Therefore, the controller 320 can diagnose the abnormal battery units among the multiple battery units 110, 120, ..., 130 based on the first deviation value (D1) and the second deviation value (D2).

[0085] According to the embodiment, the controller 320 can manage a plurality of battery units 110, 120, ..., 130 based on a distribution (P) of at least one standard deviation (D) of a plurality of vehicles 10 and 20. Here, the distribution (P) of standard deviations (D) of a plurality of vehicles 10 and 20 may mean the distribution of standard deviations calculated for each of the plurality of vehicles 10 and 20. For example, the distribution (P) of standard deviations of a plurality of vehicles 10 and 20 may mean the degree of dispersion of the standard deviations (D) of vehicle 10, ... and the standard deviations (D) of vehicle 20.

[0086] According to the embodiment, the controller 320 can calculate the distribution (P) of the standard scores of multiple vehicles 10 and 20 based on any statistical analysis method. Here, the statistical analysis method can include the analysis method using the standard normal distribution and the IQR (Interquartile Range) analysis method. Here, the IQR (Interquartile Range) analysis method may mean the interquartile range analysis method. The interquartile range may mean the range of the middle 50% of all data, i.e., the range between the first and third quartiles of the data (25% to 75%). The controller 320 can calculate the degree of dispersion of the standard scores of multiple vehicles 10 and 20 by various statistical analysis methods and can detect outliers.

[0087] The deviation scores of multiple vehicles 10 and 20 do not differ significantly from the average value for all vehicles, while the deviation score of vehicle 10 containing a defective battery unit (e.g., 110) may show a large deviation. Therefore, the controller 320 can diagnose vehicle 10 containing a defective battery unit (e.g., 110) by detecting anomalies from the distribution (P) of deviation scores. Thus, the controller 320 can diagnose both vehicles containing abnormal battery units and abnormal battery units based on the distribution (P) of deviation scores of multiple vehicles 10 and 20.

[0088] According to the embodiment, the distribution (P) of at least one standard score of the multiple vehicles 10 and 20 may include a first distribution (P1) and a second distribution (P2). Here, the first distribution (P1) may be the distribution relating to the first standard score (D1) of each of the multiple vehicles 10 and 20, and the second distribution (P2) may be the distribution relating to the second standard score (D2) of each of the multiple vehicles 10 and 20. For example, the controller 320 can calculate the first distribution (P1) of the multiple vehicles 10 and 20 based on the first standard score (D1) of the multiple vehicles 10 and 20. The controller 320 can also calculate the second distribution (P2) of the multiple vehicles 10 and 20 based on the second standard score (D2) of the multiple vehicles 10 and 20.

[0089] According to one embodiment, the controller 320 can diagnose abnormal vehicles and abnormal battery units based on the distribution (P) of deviation values ​​of a plurality of vehicles 10 and 20. Here, an abnormal vehicle may mean a vehicle containing an abnormal battery unit. According to one embodiment, the controller 320 can diagnose a vehicle as abnormal if, in at least one distribution (P) of deviation values ​​of a plurality of vehicles 10 and 20, the deviation value is greater than or equal to a threshold (TH). The threshold (TH) may be a reference value for detecting abnormal values ​​from the distribution (P) of deviation values.

[0090] According to the embodiment, the controller 320 can determine a threshold (TH) using the IQR (Interquartile Range) analysis method. According to the embodiment, the controller 320 can determine an IQR outlier (i.e., a value greater than 1.5 times the interquartile range) as the threshold (TH) in the distribution (P) of the deviation values ​​of multiple vehicles 10 and 20.

[0091] According to the embodiment, the controller 320 can determine a first threshold (TH1) in the first distribution (P1) and a second threshold (TH2) in the second distribution (P2). For example, the threshold (TH) may differ between the first distribution (P1) and the second distribution (P2).

[0092] Therefore, the controller 320 can diagnose a vehicle with a faulty battery unit as a faulty vehicle if its fault score is greater than or equal to a threshold (TH) in at least one distribution (P) of the fault scores of multiple vehicles 10 and 20. For example, in the first distribution (P1), if the first fault score (D1) of vehicle 10 is greater than or equal to the first threshold (TH1), the controller 320 can diagnose vehicle 10 as a faulty vehicle. Also, in the second distribution (P2), if the second fault score (D2) of vehicle 10 is greater than or equal to the second threshold (TH2), the controller 320 can diagnose vehicle 10 as a faulty vehicle.

[0093] According to the embodiment, the controller 320 can diagnose a battery unit (e.g., 110) corresponding to an abnormal value in the first distribution (P1) as being in a capacity abnormal state. For example, among a plurality of battery units 110, 120, ..., 130 included in the abnormal vehicle 10, the controller 320 can diagnose the battery unit (e.g., 110) with the largest cumulative voltage change as being in a capacity abnormal state. The cumulative voltage change of the battery unit with a capacity abnormality (e.g., 110) can be larger than the cumulative voltage change of the normal battery units (e.g., 120, ..., 130). Therefore, the controller 320 can diagnose the battery unit 110 with the largest cumulative voltage change as being in a capacity abnormal state.

[0094] According to the embodiment, the controller 320 can diagnose a battery unit (e.g., 130) corresponding to an abnormal value in the second distribution (P2) as being in an insulation abnormal state. For example, among a plurality of battery units 110, 120, ..., 130 included in the abnormal vehicle 10, the controller 320 can diagnose the battery unit (e.g., 130) with the smallest cumulative voltage change as being in an insulation abnormal state. The cumulative voltage change of the battery unit with an insulation abnormality (e.g., 130) can be smaller than the cumulative voltage change of the normal battery units (e.g., 110, ..., 120). Therefore, the controller 320 can diagnose the battery unit 130 with the smallest cumulative voltage change as being in an insulation abnormal state.

[0095] Figure 6 is a flowchart showing the operation of a battery diagnostic device according to one embodiment disclosed in this document. Referring to Figure 6, the battery diagnostic device 3000 includes the steps of: (S101) the voltage acquisition unit 310 acquiring voltage information for each of the multiple battery units 110, 120, ..., 130 contained in each of the multiple vehicles 10 and 20; and the controller 320 calculating the cumulative voltage change amount (V) for each of the multiple battery units 110, 120, ..., 130 based on the voltage information. △tot Step (S102) to calculate the cumulative voltage change (V) for each of the multiple vehicles 10 and 20, and △totThe steps include (S103) calculating at least one deviation score (D) which is the deviation between the vehicles 10 and 20, and (S104) managing the plurality of battery units 110, 120, ..., 130 based on the distribution (P) of at least one deviation score (D) of the plurality of vehicles 10 and 20.

[0096] In step S101, the voltage acquisition unit 310 can acquire voltage information for each of the multiple battery units 110, 120, ..., 130 contained in each of the multiple vehicles 10 and 20 (S101).

[0097] In step S102, the controller 320 calculates the cumulative voltage change (V) of each of the plurality of battery units 110, 120, ..., 130 based on the voltage information. △tot ) can be calculated (S102). According to the embodiment, the controller 320 calculates the voltage change amount (V) of each of the plurality of battery units 110, 120, ..., 130 based on the voltage information. △ ) calculate the voltage change (V △ Based on this, the cumulative voltage change (V △tot It is possible to calculate ).

[0098] In step S103, the controller 320 calculates the cumulative voltage change (V) for each of the multiple vehicles 10 and 20. △tot At least one standard score (D), which is the deviation between ) can be calculated (S103).

[0099] In step S104, the controller 320 can manage the plurality of battery units 110, 120, ..., 130 based on the distribution (P) of at least one deviation value (D) of the plurality of vehicles 10 and 20 (S104).

[0100] Figure 7 is a flowchart showing the operation of a controller according to one embodiment disclosed in this document. Referring to Figure 7, the controller 320 measures the cumulative voltage change (V) of each of the multiple battery units 110, 120, ..., 130.△tot ) to calculate the cumulative voltage change amount (V for each of the plurality of vehicles 10 and 20 △tot ) to calculate a first deviation value (D1), which is the deviation between the cumulative voltage change amounts (V for each of the plurality of vehicles 10 and 20 (S202); to calculate a first distribution (P1) of the plurality of vehicles 10 and 20 based on the first deviation value (D1) (S204); to diagnose an abnormal vehicle 10 based on the first distribution (P1) (S206); among the plurality of battery units 110, 120,..., 130 included in the abnormal vehicle 10, to diagnose the battery unit 110 with the largest cumulative voltage change amount as being in a capacity abnormal state (S208); and it can include.

[0101] Also, referring to FIG. 7, the controller 320 calculates the cumulative voltage change amount (V for each of the plurality of battery units 110, 120,..., 130 △tot ) to calculate a second deviation value (D2), which is the deviation between the cumulative voltage change amounts (V for each of the plurality of vehicles 10 and 20 (S203); to calculate a second distribution (P2) of the plurality of vehicles 10 and 20 based on the second deviation value (D2) (S205); to diagnose an abnormal vehicle 10 based on the second distribution (P2) (S207); among the plurality of battery units 110, 120,..., 130 included in the abnormal vehicle 10, to diagnose the battery unit 130 with the smallest cumulative voltage change amount as being in an insulation abnormal state (S209); and it can include.

[0102] In step S201, the controller 320 can calculate the cumulative voltage change amount (V for each of the plurality of battery units 110, 120,..., 130 (S201). According to an embodiment, the controller 320 calculates the cumulative voltage change amount (V for each of the plurality of battery units 110, 120,..., 130 based on the voltage information of each of the plurality of battery units 110, 120,..., 130 included in each of the plurality of vehicles 10 and 20 △tot ) can be calculated. △tot ) can be calculated.

[0103] ​​In steps S202 and S203, the controller 320 calculates the cumulative voltage change (V) for each of the multiple vehicles 10 and 20. △tot The first standard score (D1) or the second standard score (D2), which is the deviation between the two values, can be calculated (S202, S203).

[0104] In steps S204 and S205, the controller 320 can calculate the first distribution (P1) of the multiple vehicles 10 and 20 based on the first standard score (D1) (S204). The controller 320 can also calculate the second distribution (P2) of the multiple vehicles 10 and 20 based on the second standard score (D2) (S205).

[0105] In steps S206 and S207, the controller 320 can diagnose an abnormal vehicle 10 based on a first distribution (P1) or a second distribution (P2) of multiple vehicles 10 and 20 (S206, S207).

[0106] In steps S208 and S209, the controller 320 can diagnose battery unit 110, which has the largest cumulative voltage change, as having a capacity abnormality, and battery unit 130, which has the smallest cumulative voltage change, as having an insulation abnormality, among the multiple battery units 110, 120, ..., 130 included in the abnormal vehicle 10 (S208, S209).

[0107] Figure 8 is a block diagram showing the hardware configuration of a computing system that implements the operation method of a battery management device according to one embodiment disclosed in this document.

[0108] Referring to Figure 8, the computing system 4000 of the battery diagnostic device 3000 according to one embodiment disclosed herein may include an MCU 4100, a memory 4200, an input / output I / F 4300, and a communication I / F 4400. However, this is merely illustrative, and various embodiments are not limited thereto. For example, at least one of the components of the battery diagnostic device 3000 described above may be omitted, or one or more other components (e.g., an input device, at least one sensor, a power management device, etc.) may be added to the configuration of the battery diagnostic device 3000. Also, at least one of the components described above may be integrated with other components.

[0109] The MCU4100 may be a processor that executes various programs (for example, a battery voltage analysis program) stored in the memory 4200, processes various data through such programs, and performs the functions of the battery diagnostic device 3000 shown in Figure 1 above.

[0110] According to the embodiment, the MCU 4100 can control at least one other component of the battery diagnostic device 3000 (for example, the memory 4200, the input / output I / F 4300, and the communication I / F 4400) and perform various information processing or calculations.

[0111] According to the embodiment, the MCU 4100 can execute software stored in the memory 4200 and control at least one other component (e.g., hardware or software component) of the battery diagnostic device 3000 connected to the MCU 4100, thereby enabling the operation of the battery diagnostic device 3000.

[0112] The memory 4200 can store various programs related to the operation of the battery diagnostic device 3000. The memory 4200 can also store the operation data of the battery diagnostic device 3000.

[0113] According to the embodiment, the memory 4200 can store information acquired from the communication I / F 4400. For example, the memory 4200 can store voltage information acquired during the charge-discharge intervals of a plurality of battery units 110, 120, ..., 130. According to the embodiment, the memory 4200 can store one or more programs used in the mathematical or logical calculation processes of the battery diagnostic device 3000. For example, the memory 4200 may include a program related to an IQR (Interquartile Range) analysis method or a statistical data analysis method.

[0114] Multiple such memory 4200s may be provided as needed. The memory 4200 may be volatile or non-volatile. As volatile memory, RAM, DRAM, SRAM, etc., can be used. As non-volatile memory, ROM, PROM, EAROM, EPROM, EEPROM, flash memory, etc., can be used. The examples of memory 4200 listed above are merely illustrative and the system is not limited to these examples.

[0115] The I / O I / F 4300 can provide an interface that connects input devices (not shown), such as keyboards, mice, and touch panels, with output devices (not shown), such as displays, and the MCU 4100, enabling data transmission and reception.

[0116] The communication I / F 4400 can establish a wired communication channel and / or a wireless communication channel between the battery diagnostic device 3000 and other devices, and can send and receive information via the established communication channel. According to the embodiment, the communication I / F 4400 can receive information from a communication module (not shown) included in the battery management device 200. For example, the communication I / F 4400 of the battery diagnostic device 3000 can receive information related to the battery unit 110. Here, the information related to the battery unit 110 may include at least one of the following: unique identification number information, type information, usage cycle information, voltage information, current information, temperature information, resistance information, charge depth information, SOC information, and C-rate information.

[0117] According to the embodiment, the connection between the communication I / F 4400 of the battery diagnostic device 3000 and the communication module (not shown) of the battery management device 200 may be a communication connection via a wired and / or wireless network. In one embodiment, the wired network may be based on LAN (local area network) communication or 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).

[0118] According to this embodiment, the connection between the communication I / F 4400 of the battery diagnostic device 3000 and the communication module (not shown) of the battery management device 200 may be a connection via a communication method between devices (for example, a bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)).

[0119] Although all components constituting the embodiments disclosed in this document have been described as operating either as a single unit or in combination, 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 components may operate in combination of one or more units.

[0120] Furthermore, terms such as “includes,” “constitutes,” or “possesses,” as described above, mean that they may contain the component in question, and not exclude other components, unless otherwise specified. All terms, including technical or scientific terms, have the same meaning as those generally understood by a person of ordinary skill in the art to which the embodiments disclosed herein belong, unless otherwise specified. Commonly used terms, such as those defined in dictionaries, should be interpreted to be consistent with their meaning in the context of the relevant technology, and not to be interpreted in an ideal or overly formal sense unless explicitly defined herein.

[0121] The aforementioned disclosures provide a general overview of some embodiments so that those skilled in the art may better understand the aspects of this disclosure. Those skilled in the art will understand that this disclosure can be readily used as a basis for designing or modifying other structures to achieve the same purpose or benefits as the embodiments introduced herein. Furthermore, those skilled in the art will recognize that such equivalent configurations can be modified, substituted, and otherwise adapted within this specification without departing from the scope of this disclosure.

Claims

1. A voltage acquisition unit that acquires voltage information for each of the multiple battery units contained in each of the multiple vehicles, Based on the voltage information, the cumulative voltage change amount for each of the multiple battery units is calculated. For each of the aforementioned multiple vehicles, at least one deviation value, which is the deviation between the cumulative voltage change amounts, is calculated. A controller that manages the plurality of battery units based on the distribution of at least one deviation value of the plurality of vehicles, Battery diagnostic device, including

2. The battery diagnostic device according to claim 1, wherein the at least one deviation value for each of the plurality of vehicles includes at least one of the first deviation value and the second deviation value.

3. The aforementioned controller, The battery diagnostic device according to claim 2, wherein the first deviation value is calculated by dividing the difference between the maximum and median values ​​of the cumulative voltage change amount of each of the multiple battery units contained in each of the multiple vehicles by the standard deviation of the cumulative voltage change amount of each of the multiple battery units.

4. The aforementioned controller, The battery diagnostic device according to claim 2, wherein the second deviation value is calculated by dividing the difference between the minimum and median values ​​of the cumulative voltage change amount of each of the multiple battery units contained in each of the multiple vehicles by the standard deviation of the cumulative voltage change amount of each of the multiple battery units.

5. The aforementioned controller, Based on the first standard score, the first distribution of the multiple vehicles is calculated. The battery diagnostic device according to claim 2, which calculates a second distribution of the plurality of vehicles based on the second deviation score.

6. The aforementioned controller, A battery diagnostic device according to any one of claims 1 to 5, wherein, in the distribution of the deviation values ​​of at least one of the plurality of vehicles, a vehicle whose deviation value is above a threshold is diagnosed as an abnormal vehicle containing an abnormal battery unit.

7. The aforementioned controller, The battery diagnostic device according to claim 6, which diagnoses a capacity abnormality state in a battery unit among a plurality of battery units included in the abnormal vehicle that has the largest cumulative voltage change.

8. The aforementioned controller, The battery diagnostic device according to claim 6, which diagnoses an insulation abnormality in the battery unit with the smallest cumulative voltage change among a plurality of battery units included in the abnormal vehicle.

9. The battery diagnostic device according to any one of claims 1 to 5, wherein the voltage information is the voltage acquired during the charging interval of the plurality of battery units.

10. The steps include obtaining voltage information for each of the multiple battery units contained in each of the multiple vehicles, A step of calculating the cumulative voltage change amount for each of the plurality of battery units based on the voltage information, The steps include: calculating at least one deviation value for each of the plurality of vehicles, which is the deviation between the cumulative voltage change amounts; A step of managing the plurality of battery units based on the distribution of at least one deviation value of the plurality of vehicles, Battery diagnostic methods, including those mentioned above.

11. The battery diagnostic method according to claim 10, wherein the at least one deviation value for each of the plurality of vehicles includes at least one of the first deviation value and the second deviation value.

12. The step of calculating at least one standard score is: The battery diagnostic method according to claim 11, further comprising the step of calculating the first deviation value by dividing the difference between the maximum and median values ​​of the cumulative voltage change amount for each of the multiple battery units contained in each of the multiple vehicles by the standard deviation of the cumulative voltage change amount for each of the multiple battery units.

13. The step of calculating at least one standard score is: The battery diagnostic method according to claim 11, further comprising the step of calculating the second deviation value by dividing the difference between the minimum and median values ​​of the cumulative voltage change amount for each of the multiple battery units contained in each of the multiple vehicles by the standard deviation of the cumulative voltage change amount for each of the multiple battery units.

14. A step of calculating a first distribution of the plurality of vehicles based on the first standard score, The battery diagnostic method according to claim 11, further comprising the step of calculating a second distribution of the plurality of vehicles based on the second deviation score.

15. The step of managing the aforementioned multiple battery units is: The battery diagnostic method according to any one of claims 10 to 14, further comprising the step of diagnosing a vehicle whose deviation value is greater than or equal to a threshold in the distribution of deviation values ​​of the plurality of vehicles as an abnormal vehicle containing an abnormal battery unit.

16. The battery diagnostic method according to claim 15, further comprising the step of diagnosing a battery unit with the largest cumulative voltage change among a plurality of battery units included in the abnormal vehicle as being in a capacity abnormal state.

17. The battery diagnostic method according to claim 15, further comprising the step of diagnosing a battery unit with the smallest cumulative voltage change among a plurality of battery units included in the abnormal vehicle as being in an insulation abnormal state.

18. The battery diagnostic method according to any one of claims 10 to 14, wherein the voltage information is the voltage acquired during the charging interval of the plurality of battery units.

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