Battery diagnosis device and operation method therefor

Abstract

A battery diagnosis device according to one embodiment disclosed in the present specification may comprise: an interface for acquiring a plurality of open circuit voltage (OCV) data for a battery unit; and one or more processors for acquiring a plurality of estimated states of charge (SOC) corresponding to at least a part of the OCV data, acquiring a plurality of estimated states of health (SOH) corresponding to at least a part of the plurality of estimated SOC, and diagnosing a degree of occurrence of cathode capacity loss of the battery unit on the basis of a specific estimated SOH satisfying a threshold SOH condition among the estimated SOH.

Description

Battery diagnostic device and its operation method

[0001] Cross-citation with related applications

[0002] The present invention claims the benefit of priority based on Korean Patent Application No. 10-2025-0007936 filed on January 20, 2025, Korean Patent Application No. 10-2025-0007937 filed on January 20, 2025, and Korean Patent Application No. 10-2026-0008886 filed on January 16, 2026, and includes all contents disclosed in the documents of said Korean patent applications as part of this specification.

[0003] Technology field

[0004] The embodiments disclosed in this document relate to a battery diagnostic device and a method of operating the same.

[0005] Recently, active research and development on secondary batteries has been underway. Here, secondary batteries refer to rechargeable batteries, encompassing conventional Ni / Cd and Ni / MH batteries as well as the more recent lithium-ion batteries. Among secondary batteries, lithium-ion batteries have the advantage of significantly higher energy density compared to conventional Ni / Cd and Ni / MH batteries. Furthermore, lithium-ion batteries can be manufactured in a compact and lightweight manner, making them suitable for use as power sources for mobile devices. Recently, their scope of application has expanded to include electric vehicles, drawing attention as a next-generation energy storage medium.

[0006] In addition, the secondary battery can generally be used as a battery pack comprising a battery module in which a plurality of battery cells are connected in series and / or parallel. Also, the secondary battery can be used as a battery rack comprising a plurality of battery modules and a rack frame that accommodates these battery modules.

[0007] Such battery cells, battery modules, battery packs, or battery racks can be utilized in various devices. For example, batteries can be used in mobile devices such as mobile phones, laptop computers, smartphones, and smart pads, as well as in fields such as electric vehicles (EVs, HEVs, PHEVs) and large-capacity energy storage systems (ESS).

[0008] The status and operation of these batteries can be managed and controlled by a battery management system (BMS). The battery management system can be included together with the batteries within a single device.

[0009] In addition, the battery management system can manage and control the battery while 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 a vehicle, etc., and manage and control the battery by utilizing the collected data.

[0010] If a short circuit or other type of failure occurs inside the battery, the risk of damage to devices containing the battery (e.g., EV, ESS) may increase. Accordingly, there is a need for a method to detect abnormal conditions of the battery and reduce the risk of damage to devices containing the battery.

[0011] The embodiments disclosed in this document may provide a battery diagnostic device and a method of operation thereof that can diagnose abnormalities in a battery unit based on OCV data of the battery unit.

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

[0013] A battery diagnostic device according to one embodiment disclosed in this document may include: an interface for acquiring a plurality of Open Circuit Voltage (OCV) data for a battery unit; and one or more processors for acquiring a plurality of State of Charge (SOC) corresponding to at least some of the OCV data, acquiring a plurality of State of Health (SOH) corresponding to at least some of the plurality of State of Health, and diagnosing the degree of occurrence of positive capacity loss of the battery unit based on a specific State of Health that satisfies a threshold SOH condition among the estimated SOHs.

[0014] In a battery diagnostic device according to one embodiment disclosed in this document, one or more processors can obtain at least one first estimated SOC included in a first SOC interval among the estimated SOCs, obtain a specific estimated SOH among at least one first estimated SOH corresponding to the first estimated SOC that satisfies a threshold SOH condition, and diagnose the degree of occurrence of positive capacity loss of a battery unit based on the specific estimated SOH.

[0015] In a battery diagnostic device according to one embodiment disclosed in this document, one or more processors can diagnose the degree of occurrence of positive capacity loss of a battery unit based on a specific estimated SOH and a first reference SOH.

[0016] In a battery diagnostic device according to one embodiment disclosed in this document, a specific estimated SOH may be an SOH having a maximum value among the first estimated SOHs.

[0017] In a battery diagnostic device according to one embodiment disclosed in this document, one or more processors can obtain a plurality of estimated SOHs by performing a process for at least some of the plurality of estimated SOCs to obtain a k-th estimated SOH corresponding to the k-th estimated SOC based on (i) a k-th estimated SOC among a plurality of estimated SOCs, (ii) a k-th charge amount or a k-th discharge amount corresponding to the k-th estimated SOC, and (iii) a (k+1)-th estimated SOC which is the result of charging a battery unit corresponding to the k-th estimated SOC by a k-th charge amount or discharging a k-th discharge amount.

[0018] In a battery diagnostic device according to one embodiment disclosed in this document, one or more processors can obtain a plurality of estimated SOCs corresponding to at least a portion of OCV data based on an OCV-SOC table corresponding to a reference battery unit.

[0019] In a battery diagnostic device according to one embodiment disclosed in this document, one or more processors can obtain an estimated SOH corresponding to an estimated SOC based on a current integration method.

[0020] In a battery diagnostic device according to one embodiment disclosed in this document, a plurality of OCV data may be specific OCV data corresponding to a driving range greater than or equal to a first driving distance and less than a second driving distance among OCV data corresponding to the driving distance of a mobile body equipped with a battery unit.

[0021] In a battery diagnostic device according to one embodiment disclosed in this document, the interface can acquire the OCV data in real time from a mobile body equipped with the battery unit.

[0022] A battery diagnostic method according to one embodiment disclosed in this document may include: acquiring a plurality of Open Circuit Voltage (OCV) data for a battery unit; acquiring a plurality of State of Charge (SOC) corresponding to at least some of the OCV data; acquiring a plurality of State of Health (SOH) corresponding to at least some of the plurality of State of Health; and diagnosing the degree of occurrence of positive capacity loss of the battery unit based on a specific State of Health that satisfies a critical SOH condition among the estimated SOHs.

[0023] In a battery diagnostic method according to one embodiment disclosed in this document, the operation of obtaining a plurality of estimated SOCs includes the operation of obtaining at least one first estimated SOC included in a first SOC interval among the estimated SOCs, and the operation of obtaining a plurality of estimated SOHs includes the operation of obtaining a specific estimated SOH among at least one first estimated SOH corresponding to the first estimated SOC that satisfies a threshold SOH condition, and the operation of diagnosing the degree of occurrence of positive capacity loss of a battery unit may include the operation of diagnosing the degree of occurrence of positive capacity loss of a battery unit based on the specific estimated SOH.

[0024] In a battery diagnostic method according to one embodiment disclosed in this document, the operation of diagnosing the degree of occurrence of positive capacity loss of a battery unit may include the operation of diagnosing the degree of occurrence of positive capacity loss of a battery unit based on a specific estimated SOH and a first reference SOH.

[0025] In a battery diagnostic method according to one embodiment disclosed in this document, the operation of obtaining a plurality of estimated SOHs may include the operation of obtaining a plurality of estimated SOHs by performing a process for at least some of the plurality of estimated SOCs to obtain a k-th estimated SOH corresponding to the k-th estimated SOC based on (i) a k-th estimated SOC among a plurality of estimated SOCs, (ii) a k-th charge amount or a k-th discharge amount corresponding to the k-th estimated SOC, and (iii) a (k+1)-th estimated SOC which is the result of charging a battery unit corresponding to the k-th estimated SOC by a k-th charge amount or discharging a k-th discharge amount.

[0026] In a battery diagnostic method according to one embodiment disclosed in this document, the operation of obtaining a plurality of estimated SOHs may include the operation of obtaining a plurality of estimated SOCs corresponding to at least some of the OCV data based on an OCV-SOC table corresponding to a reference battery unit.

[0027] According to one embodiment disclosed in this document, a computer-readable medium is provided that records a program for executing the battery diagnostic method on a computer.

[0028] According to the embodiments disclosed in this document, abnormalities in a battery unit can be diagnosed based on the OCV data of the battery unit.

[0029] According to the embodiments disclosed in this document, the degree of occurrence of positive capacity loss can be diagnosed based on the OCV data of the battery unit.

[0030] In addition, various effects that can be identified directly or indirectly through this document may be provided.

[0031] FIG. 1 is a block diagram showing a battery pack according to one embodiment disclosed in this document.

[0032] FIG. 2 is a block diagram showing a battery diagnostic device according to one embodiment disclosed in this document.

[0033] FIGS. 3a and 3b are drawings for explaining the process of estimating the SOH corresponding to the battery unit.

[0034] Figures 4 and 5 are drawings showing the estimated SOH corresponding to each of the multiple estimated SOCs.

[0035] FIG. 6 is a flowchart showing the operation of a battery diagnostic device according to one embodiment disclosed in this document.

[0036] FIG. 7 is a block diagram showing the hardware configuration of a computing system for performing the operation method of a battery diagnostic device according to one embodiment disclosed in this document.

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

[0038] The various embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments.

[0039] In relation to the description, similar reference numerals may be used for similar or related components. The singular form of the noun corresponding to an item may include one or more of the said item unless the relevant context clearly indicates otherwise.

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

[0041] In this document, where it is mentioned that any (e.g., 1) component is “connected,” “coupled,” or “joined” to another (e.g., 2) component, with or without the terms “functionally” or “communicationly,” or where it is mentioned as “coupled” or “connected,” it means that said component may be connected to said other component directly (e.g., by wire), wirelessly, or through a third component.

[0042] According to one embodiment, the method according to the various embodiments disclosed herein may be provided as included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or distributed online (e.g., download or upload) through 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 temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0043] According to various embodiments, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to various embodiments, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or 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 corresponding component among the multiple components prior to integration. According to various embodiments, operations performed by the module, program, or other components 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.

[0044] FIG. 1 is a block diagram showing a battery pack according to one embodiment disclosed in this document.

[0045] Referring to FIG. 1, the battery pack (1) may include an upper battery unit (12), a sensor unit (14), a switching unit (16), and a battery management system (BMS) (20). At this time, the battery pack (1) may be equipped with a plurality of upper battery units (12), sensor units (14), switching units (16), and battery management systems (20).

[0046] According to an embodiment, the upper battery unit (12) can supply power to a target device (not shown). To this end, the upper battery unit (12) may be electrically connected to the target device. Here, the target device may include an electrical, electronic, or mechanical device that operates by receiving power from the battery pack (1). For example, the target device may be an electric vehicle (EV), but is not limited thereto.

[0047] According to an embodiment, the upper battery unit (12) may include at least one battery unit (10) capable of charging and discharging. In this case, the battery unit (10) may be a battery cell (10) or a battery bank (10), and the battery cell (10) or battery bank (10) may be a basic unit capable of charging and discharging electrical energy. For example, the battery cell (10) or battery bank (10) may be a lithium-ion (Li-ion) battery, a lithium-ion polymer (Li-ion polymer) battery, a nickel-cadmium (Ni-Cd) battery, a nickel-hydrogen (Ni-MH) battery, etc., but is not limited thereto.

[0048] According to an embodiment, a plurality of upper battery units (12) may be connected in series or in parallel. For example, the upper battery units (12) may be battery modules, battery banks, battery cells, or a set of battery cells (cell-to-pack structure).

[0049] According to an embodiment, the sensor unit (14) can obtain information related to the upper battery unit (12). According to an embodiment, the sensor unit (14) can obtain values ​​(or information) related to the state of each upper battery unit (12). In one embodiment, the values ​​related to the state may include one or more values ​​for the voltage, current, resistance, state of charge (SOC), state of health (SOH), or temperature of the battery cell, or a combination thereof.

[0050] According to the embodiment, the sensor unit (14) can provide information of each of the plurality of upper battery units (12) to the battery management system (20).

[0051] According to an embodiment, the switching unit (16) may include a component for controlling the current flow for charging or discharging the upper battery unit (12). For example, the switching unit (16) may include at least one relay and / or magnetic contactor, etc., depending on the specifications of the battery pack (1).

[0052] According to an embodiment, the battery management system (BMS) (20) can monitor the voltage, current, temperature, etc. of the battery pack (1) and control or manage the battery pack (1) to prevent overcharging and over-discharging. For example, the battery management system (20) may include a plurality of terminals as an interface that receives values ​​measured by the various parameters described above, and a circuit connected to these terminals to perform processing of the received values. Additionally, the battery management system (20) may control the sensor unit (14) and / or the switching unit (16). For example, the battery management system (20) may be connected to a plurality of upper battery units (12) to monitor the status of each of the plurality of upper battery units (12) and control the ON / OFF of relays or contactors.

[0053] According to the embodiment, the operation of the battery management system (20) can be performed by a Battery Management System (BMS) in the vehicle, as well as by various devices such as a server, cloud, charger, or charger / discharger.

[0054] The upper controller (2) can transmit control signals for a plurality of upper battery units (12) to the battery management system (20). Accordingly, the operation of the battery management system (20) can be controlled based on the signals applied from the upper controller (2).

[0055] According to an embodiment, the battery management system (20) may include the battery diagnostic device (100) of FIG. 2. According to another embodiment, the battery management system (20) may be a different system from the battery diagnostic device (100) of FIG. 2. That is, the battery diagnostic device (100) of FIG. 2 may be included in the battery pack (1) or may be configured as another device outside the battery pack (1). For convenience of explanation, the following description assumes that the battery diagnostic device (100) is configured as another device outside the battery pack (1). Furthermore, the operation of the battery diagnostic device (100) below may be performed by a Battery Management System (BMS) within the vehicle, as well as by various devices such as a server, cloud, charger, or charger / discharger.

[0056] FIG. 2 is a block diagram showing a battery diagnostic device according to an embodiment disclosed in this document. FIG. 3a and 3b are diagrams for explaining the process of estimating the SOH corresponding to a battery unit, and FIG. 4 and 5 are diagrams showing the estimated SOH corresponding to each of a plurality of estimated SOCs. The operation of the battery diagnostic device (100) illustrated in FIG. 2 can be described in detail below with reference to FIG. 3a to 5 together.

[0057] First, referring to FIG. 2, a battery diagnostic device (100) according to one embodiment disclosed in this document can diagnose an abnormality of at least one battery unit.

[0058] According to an embodiment, the battery diagnostic device (100) may include an interface (110) and one or more processors (120) to diagnose abnormalities in a battery unit. However, it is not limited thereto, and other components may be further included in the battery diagnostic device (100), and two or more components may be integrated into one, or one component may be divided into two or more components.

[0059] According to an embodiment, the interface (110) can obtain status information related to the battery unit. Here, the interface (110) may refer to a configuration capable of communicating with an external device via wired and / or wireless means. For example, the status information may include voltage information, current information, temperature information, or resistance information of each battery unit.

[0060] According to an embodiment, the interface (110) can obtain voltage information and / or current information by communicating with a sensor unit (14, see FIG. 1). Additionally, the interface (110) can obtain voltage information and / or current information by communicating with other infrastructure such as a BMS (20, see FIG. 1) or a server and cloud.

[0061] According to an embodiment, the interface (110) can obtain Open Circuit Voltage (OCV) data of the battery unit.

[0062] According to an embodiment, the interface (110) can acquire OCV data for each of the multiple charging processes for the battery unit. For example, the interface (110) can acquire OCV data before the start of charging and OCV data after the end of charging for each charging process for the battery unit. For example, the interface (110) can acquire OCV data for the battery unit during the process of charging the battery unit to have a rest period of a predetermined time (e.g., 1 hour) for each predetermined SOC. For example, the interface (110) can acquire OCV data at the battery unit's SOC 0%, 10%, 20%, ..., 70%, 80%.

[0063] According to an embodiment, the interface (110) can acquire OCV data for each of the multiple charge / discharge processes for the battery unit. For example, the interface (110) can acquire OCV data before the start of charging and OCV data after the end of charging for each charge process for the battery unit, and can acquire OCV data before the start of discharging and OCV data after the end of discharging for each discharge process (e.g., a discharge process due to driving of a vehicle equipped with a battery unit). For example, the interface (110) can acquire OCV data corresponding to one charge / discharge cycle for the battery unit. For example, the interface (110) can acquire OCV data when the operation of the vehicle equipped with the battery unit is stopped (rest) or when the engine is started (key-on).

[0064] According to an embodiment, the interface (110) can obtain OCV data classified by driving distance intervals of a mobile body equipped with a battery unit. For example, the interface (110) can obtain OCV data corresponding to one charge / discharge cycle in a specific driving distance interval of the mobile body (e.g., 100,000 km to 110,000 km).

[0065] According to an embodiment, the interface (110) can acquire OCV data in real time from a mobile body equipped with a battery unit. For example, the interface (110) can acquire OCV data from a charger or charger when OCV data is generated according to the driving and charging of the mobile body, and the mobile body is connected to a charger or charger / discharger and OCV data is transmitted from the mobile body to the charger or charger / discharger. As another example, the interface (110) can acquire OCV data from the mobile body through the cloud.

[0066] According to an embodiment, the interface (110) can acquire voltage information over time during a charging period, a resting period after charging, a discharging period, and / or a resting period after discharging of the battery unit. According to an embodiment, the interface (110) may include a voltage monitoring circuit or a sensor.

[0067] According to an embodiment, one or more processors (120) can perform operations of the battery diagnostic device (100). For example, one or more processors (120) can manage the operation of the upper battery unit by processing data obtained from the interface (110). According to an embodiment, one or more processors (120) can diagnose an abnormality in the battery unit based on OCV data obtained from the interface (110).

[0068] According to an embodiment, one or more processors (120) can diagnose an abnormality in a battery unit based on at least some of the OCV data.

[0069] For reference, data related to abnormalities (e.g., degradation) of the battery unit may include at least one of the battery unit's residual energy, battery unit's state of health (SOH), battery unit's retention, battery unit's resistance growth rate, battery unit's cathode active material (LAMc; LAMp), battery unit's anode active material (LAMa; LAMn), battery unit's available lithium inventory (LLI), or any combination thereof. However, the embodiments of this document are not limited to those described above.

[0070] For example, anode capacity loss may refer to a parameter indicating the degree to which the active material within the anode of a battery unit decreases as the battery unit is used. For instance, anode capacity loss may occur due to phenomena such as the degree of disorder in the crystal structure within the battery unit and the destruction of particles within the anode.

[0071] Furthermore, cathode capacity loss can refer to a parameter indicating the degree to which the reaction surface area of ​​the cathode active material decreases due to the accumulation of byproducts on the surface of the cathode active material or by-reactants such as gases as the battery unit is used. For example, cathode capacity loss can occur due to phenomena such as the degree of disorder in the crystal structure within the battery unit and the destruction of particles within the cathode.

[0072] In addition, available lithium loss may mean a decrease in the amount of lithium ions available to participate in chemical reactions during the charging and discharging process of the battery.

[0073] Below, in order to help understand the method of diagnosing the extent of positive capacity loss and / or the extent of available lithium loss by a battery diagnostic device according to one embodiment disclosed in this document, we will first describe the case where only positive capacity loss occurs and the case where only available lithium loss occurs in a battery unit with reference to FIGS. 3a and 3b.

[0074] First, FIG. 3a is a diagram illustrating the process of estimating the SOH of a battery unit (EOL) when only a positive capacity loss (10%) occurs in the battery unit (EOL; End of Life). For reference, as shown in FIG. 3a, when only a positive capacity loss occurs in the battery unit (EOL), the shape of the voltage-capacity data (OCV-SOC table) of the battery unit (EOL) may show a shape that shrinks (shrinks to the left) compared to the shape of the voltage-capacity data (OCV-SOC table) of the reference battery unit (BOL (Beginning of Life) battery unit).

[0075] Referring to Fig. 3a, as previously mentioned, since it is difficult to obtain an accurate OCV-SOC table for each battery unit (EOL) undergoing real-time degradation, the SOC of the battery unit (EOL) is estimated based on the OCV-SOC table of the reference battery unit (BOL). When the voltage (OCV) of the battery unit (EOL) is 3.6V and when fully charged (4.1V), the estimated capacity is calculated to be 50Ah and 100Ah, respectively. Therefore, it can be seen that the estimated SOC (SOCstart) when the voltage of the battery unit (EOL) is 3.6V is 50% (50 / 100), and the estimated SOC (SOCend) when fully charged is 100%. For reference, when the voltage (OCV) of the battery unit (EOL) is 3.6V, the actual capacity is 45Ah, and when fully charged, the actual capacity is 90Ah. Therefore, it can be confirmed that when the voltage of the battery unit (EOL) is 3.6V, the actual SOC (SOCstart) is 50% (45 / 90), and when fully charged, the actual SOC (SOCend) is 100%. In other words, when only positive capacity loss occurs in the battery unit (EOL), it can be confirmed that the estimated SOC (SOCstart) is the same as the actual SOC.

[0076] In addition, the SOH of the battery unit (EOL) can be estimated based on the current integration method according to Equation 1 below.

[0077] [Formula 1]

[0078] Estimated SOH = {∫i / (SOCend-SOCstart)}*(1 / BOLcapa)

[0079] For reference, ∫i represents the amount of charge (or discharge) from the start of charging (or start of discharging) t1 to the end of charging (or end of discharging) t2, SOCstart represents the estimated SOC at the start of charging (or start of discharging), SOCend represents the estimated SOC at the end of charging (or end of discharging), and BOLcapa represents the full charge capacity (i.e., 100%) of the reference battery unit (BOL).

[0080] Based on Figure 3a and Equation 1, it can be confirmed that the charge amount (∫i) for the battery unit (EOL) is 45Ah as the voltage of the battery unit (EOL) increases from 3.6V to 4.1V, and the estimated SOH of the battery unit (EOL) is {45 / (100%-50%)}*1 / 100=0.9=90%, which matches the actual SOH (90%) of the battery unit (EOL). In other words, it can be confirmed that the degree of actual positive capacity loss is reflected in the estimated SOH through the current integration method.

[0081] Meanwhile, FIG. 3b is a diagram illustrating the process of estimating the SOH of a battery unit (EOL) when only available lithium loss (10%) occurs in the battery unit (EOL; End of Life). For reference, as shown in FIG. 3b, when only available lithium loss occurs in the battery unit (EOL), the shape of the voltage-capacity data (OCV-SOC table) of the battery unit (EOL) may show a shape that is shifted (shifted upward) from the shape of the voltage-capacity data (OCV-SOC table) of the reference battery unit (BOL battery unit).

[0082] Referring to Fig. 3b, as previously mentioned, since it is difficult to obtain an accurate OCV-SOC table for each battery unit (EOL) undergoing real-time degradation, the SOC of the battery unit (EOL) is estimated based on the OCV-SOC table of the reference battery unit (BOL). When the voltage (OCV) of the battery unit (EOL) is 3.6V and when fully charged (4.1V), the estimated capacity is calculated to be 50Ah and 100Ah, respectively. Therefore, it can be seen that the estimated SOC (SOCstart) when the voltage of the battery unit (EOL) is 3.6V is 50% (50 / 100), and the estimated SOC (SOCend) when fully charged is 100%. For reference, when the voltage (OCV) of the battery unit (EOL) is 3.6V, the actual capacity is 40Ah, and when fully charged, the actual capacity is 90Ah. Therefore, it can be confirmed that when the voltage of the battery unit (EOL) is 3.6V, the actual SOC (SOCstart) is 44.44% (40 / 90), and when fully charged, the actual SOC (SOCend) is 100%. In other words, when only available lithium loss occurs in the battery unit (EOL), it can be confirmed that the estimated SOC (SOCstart) is different from the actual SOC (SOCstart).

[0083] In addition, the SOH of the battery unit (EOL) can be estimated based on the current integration method according to Equation 1.

[0084] Based on Figure 3b and Equation 1, it can be confirmed that the charge amount (∫i) for the battery unit (EOL) is 50Ah as the voltage of the battery unit (EOL) increases from 3.6V to 4.1V, and the estimated SOH of the battery unit (EOL) is {50 / (100%-50%)}*1 / 100=1=100%, which does not match the actual SOH (90%) of the battery unit (EOL). In other words, it can be confirmed that the actual amount of available lithium loss is not reflected in the estimated SOH through the current integration method.

[0085] That is, from FIGS. 3a and FIGS. 3b, it can be seen that when a positive capacity loss occurs in the battery unit (EOL), an estimated SOH identical to the actual SOH of the battery unit (EOL) is obtained, whereas when available lithium loss occurs in the battery unit (EOL), an estimated SOH different from the actual SOH of the battery unit (EOL) is obtained.

[0086] For reference, Figures 3a and 3b are illustrated with linear voltage-capacity graphs to aid in understanding why the estimated SOH differs when anode capacity loss and available lithium loss occur, respectively; however, the actual voltage-capacity graph may include non-linear sections. In this case, the actual voltage-capacity graph shows a linear graph in the SOC range of approximately 30% to 60% and in the SOC range of 70% or more. Therefore, when SOCstart is 30% to 60% or 70%, the actual degree of anode capacity loss is reflected in the estimated SOH in that range, while the actual degree of available lithium loss is not reflected in the estimated SOH. For reference, as can be seen in the aforementioned Equation 1, since SOCstart is included in the denominator of Equation 1, a large error may occur if the SOH is estimated based on an estimated SOC (SOCstart) that has an excessively large value. Accordingly, the upper and lower limits of the first SOC range may be set considering these characteristics. For example, the upper limit of the first SOC range may be 60% and the lower limit may be 30%. However, the above figures are examples to aid understanding, and the upper and lower limits may vary depending on the specifications and physical properties of the battery unit. For instance, the upper limit may be 50% and the lower limit may be 0%.

[0087] According to an embodiment, one or more processors (120) can diagnose the extent of positive capacity loss of a battery unit based on at least some of the OCV data.

[0088] According to an embodiment, one or more processors (120) can diagnose the extent of available lithium loss in a battery unit based on at least some of the OCV data.

[0089] According to an embodiment, one or more processors (120) can obtain a plurality of estimated State of Charge (SOC) corresponding to at least some of the OCV data.

[0090] According to an embodiment, one or more processors (120) can obtain a plurality of estimated SOCs corresponding to at least some of the OCV data of a battery unit (diagnosis target) based on an OCV-SOC table corresponding to a reference battery unit. For example, the reference battery unit may be a BOL battery unit.

[0091] According to an embodiment, one or more processors (120) can acquire an SOC included in a first SOC interval among the estimated SOCs as at least one first estimated SOC.

[0092] And, one or more processors (120) can obtain a plurality of estimated State of Health (SOH) corresponding to at least some of the plurality of estimated State of Health (SOC). For example, one or more processors (120) can obtain a plurality of estimated State of Health (SOH) corresponding to a first estimated State of Health (SOC).

[0093] According to an embodiment, one or more processors (120) can obtain an estimated SOH corresponding to an estimated SOC based on a current integration method according to the above-described Equation 1.

[0094] At this time, one or more processors (120) may obtain an SOCstart corresponding to OCV data at the start of charging (or start of discharging) and an SOCend corresponding to OCV data at the end of charging (or end of discharging) based on an OCV-SOC table corresponding to a reference battery unit. For example, one or more processors (120) may obtain a first_1 estimated SOC to a first_n estimated SOC based on each of the first OCV data to the nth OCV data, and obtain a first_1 estimated SOH to a first_n estimated SOH corresponding to the first_1 estimated SOC to the first_n estimated SOC based on a current integration method.

[0095] According to an embodiment, one or more processors (120) can obtain a plurality of estimated SOHs by performing a process for at least some of the plurality of estimated SOCs to obtain a k-th estimated SOH corresponding to the k-th estimated SOC based on (i) a k-th estimated SOC among a plurality of estimated SOCs, (ii) a k-th charge amount or a k-th discharge amount corresponding to the k-th estimated SOC, and (iii) a (k+1)-th estimated SOC which is the result of charging a battery unit corresponding to the k-th estimated SOC by a k-th charge amount or discharging a k-th discharge amount.

[0096] For example, one or more processors (120) can obtain a plurality of first estimated SOHs by performing a process for at least some of the plurality of first estimated SOCs to obtain a first estimated SOH corresponding to the first estimated SOC based on (i) a first_k estimated SOC among the first estimated SOCs, (ii) a first_k charge amount or a first_k discharge amount corresponding to the first estimated SOC, and (iii) a first_(k+1) estimated SOC which is the result of charging a battery unit corresponding to the first estimated SOC by the first_k charge amount or discharging by the first_k discharge amount.

[0097] Figure 4 shows the estimated SOH for multiple estimated SOC (SOCstart).

[0098] Referring to Figure 4, it can be seen that when the estimated SOC (SOCstart) is 20%, the estimated SOH is 91%, when the estimated SOC (SOCstart) is 30%, the estimated SOH is 93%, when the estimated SOC (SOCstart) is 40%, the estimated SOH is 94.8%, when the estimated SOC (SOCstart) is 50%, the estimated SOH is the maximum value of 95%, and when the estimated SOC (SOCstart) is 60%, the estimated SOH is 88%.

[0099] For example, one or more processors (120) can obtain a specific estimated SOH that satisfies a critical SOH condition among at least one first estimated SOH corresponding to a first estimated SOC. For example, one or more processors (120) can obtain a specific estimated SOH that satisfies a critical SOH condition among at least one first estimated SOH (e.g., 90%, 92%, 91%, 93%, 94.8%, 95%, 88%) corresponding to a first estimated SOC (e.g., 0%, 10%, 20%, 30%, 40%, 50%, 60%) included in a first SOC interval (e.g., interval from 0% to 60%).

[0100] According to the embodiment, the critical SOH condition may be a condition having the maximum value among the first estimated SOHs. For example, one or more processors (120) may obtain a specific estimated SOH (95%) having the maximum value among the first estimated SOHs (e.g., 90%, 92%, 91%, 93%, 94.8%, 95%, 88%).

[0101] And, one or more processors (120) can diagnose the extent of occurrence of positive capacity loss (401) and / or the extent of occurrence of available lithium loss (402) of the battery unit based on a specific estimated SOH.

[0102] According to the embodiment, one or more processors (120) can estimate the estimated SOH having the maximum value among the estimated SOHs as a degraded value due to anode capacity loss, and the estimated SOH less than the maximum value (e.g., 91%, 93%, 94.8%) as a degraded value due to anode capacity loss and additional causes (i.e., available lithium loss).

[0103] This is due to the characteristic that, as mentioned above, when only anode capacity loss occurs, an estimated SOH identical or similar to the actual SOH is obtained, whereas when available lithium loss occurs together, an estimated SOH different from the actual SOH is obtained.

[0104] Specifically, among the estimated SOH (first estimated SOH) corresponding to the first estimated SOC included in the first SOC range, the maximum SOH can be considered as a degradation value that reflects only the degree of occurrence of anode capacity loss, and the estimated SOH having a value less than the maximum SOH can be considered as a degradation value that additionally reflects additional causes (i.e., available lithium loss).

[0105] According to an embodiment, one or more processors (120) can diagnose the degree of occurrence of positive capacity loss of a battery unit based on a specific estimated SOH (i.e., an estimated SOH having a maximum value) and a first reference SOH. At this time, the first reference SOH may be the SOH of a reference battery unit (BOL battery unit), i.e., 100% SOH.

[0106] For example, as illustrated in FIG. 4, one or more processors (120) can diagnose the difference value (401) between a specific estimated SOH (i.e., an estimated SOH having a maximum value) and a first reference SOH as the degree of occurrence of positive capacity loss of the battery unit.

[0107] According to an embodiment, one or more processors (120) can diagnose the extent of available lithium loss of a battery unit based on a specific estimated SOH (i.e., an estimated SOH having a maximum value) and a second reference SOH.

[0108] According to an embodiment, one or more processors (120) can obtain a reference SOC that satisfies the reference SOC condition among the estimated SOCs, and obtain an estimated SOH corresponding to the reference SOC as a second reference SOH.

[0109] At this time, the reference SOC condition may be a condition having the minimum value among the estimated SOCs (SOCstart). For example, one or more processors (120) may acquire a 0% SOC (SOCstart) among the estimated SOCs (e.g., 0%, 10%, 20%, 30%, 40%, 50%, 60% SOCstart) as the reference SOC (SOCstart), and acquire an estimated SOH (e.g., 90%) corresponding to the reference SOC (0% SOCstart) as the second reference SOH. Then, one or more processors (120) may diagnose the degree of available lithium loss based on the difference between the specific estimated SOH and the second reference SOH. For example, as illustrated in FIG. 4, one or more processors (120) can diagnose the occurrence of available lithium loss (5%) based on the difference value (402) between a specific estimated SOH (95%) and a second reference SOH (90%).

[0110] Figure 5 shows the estimated SOH for multiple estimated SOC (SOCstart).

[0111] Referring to Figure 5, it can be seen that when the estimated SOC (SOCstart) is 10%, the estimated SOH is 94%, when the estimated SOC (SOCstart) is 30%, the estimated SOH is 95%, and when the estimated SOC (SOCstart) is 50%, the estimated SOH is 94%.

[0112] For reference, each estimated SOC can be calculated based on OCV data obtained from vehicles that have traveled a similar distance (e.g., 100,000 km to 110,000 km).

[0113] According to an embodiment, one or more processors (120) may obtain a specific estimated SOH having a maximum value (95%) among SOHs (e.g., 91%, 92%, 94%, 95%) corresponding to at least one second estimated SOC (e.g., 20%, 30%, 40%, 50%) included in a second SOC interval (e.g., 20% to 50%), and obtain a SOH having a minimum value (91%) as a second reference SOH.

[0114] Additionally, one or more processors (120) can diagnose the difference between a specific estimated SOH and a first reference SOH (100%) as the degree of occurrence of positive capacity loss (701) of the battery unit. Furthermore, one or more processors (120) can diagnose the degree of occurrence of available lithium loss based on the difference (702) between a specific estimated SOH and a second reference SOH.

[0115] FIG. 6 is a flowchart showing the operation of a battery diagnostic device according to one embodiment disclosed in this document.

[0116] Referring to FIG. 6, the battery diagnostic device (100) can acquire a plurality of Open Circuit Voltage (OCV) data for a battery unit (S101), acquire a plurality of estimated State of Charge (SOC) corresponding to at least some of the OCV data (S102), acquire a plurality of estimated State of Health (SOH) corresponding to at least some of the plurality of estimated State of Health (S103), and diagnose the degree of occurrence of positive capacity loss of the battery unit based on a specific estimated SOH that satisfies a critical SOH condition among the estimated SOHs (S104).

[0117] In step S102, the battery diagnostic device (100) can obtain at least one first estimated SOC that is included in the first SOC interval among the estimated SOCs.

[0118] In step S103, the battery diagnostic device (100) can obtain a specific estimated SOH that satisfies a threshold SOH condition among at least one first estimated SOH corresponding to the first estimated SOC. According to an embodiment, the battery diagnostic device (100) can obtain a plurality of estimated SOHs by performing a process for at least some of the plurality of estimated SOCs to obtain a k-th estimated SOH corresponding to the k-th estimated SOC based on (i) a k-th estimated SOC among a plurality of estimated SOCs, (ii) a k-th charge amount or a k-th discharge amount corresponding to the k-th estimated SOC, and (iii) a (k+1)-th estimated SOC which is the result of charging a battery unit corresponding to the k-th estimated SOC by a k-th charge amount or discharging a k-th discharge amount. According to an embodiment, the battery diagnostic device (100) can obtain a plurality of estimated SOCs corresponding to at least some of the OCV data based on an OCV-SOC table corresponding to a reference battery unit. According to an embodiment, the battery diagnostic device (100) can obtain an estimated SOH corresponding to an estimated SOC based on a current integration method.

[0119] In step S104, the battery diagnostic device (100) can diagnose the degree of occurrence of positive capacity loss of the battery unit based on a specific estimated SOH. According to an embodiment, the battery diagnostic device (100) can diagnose the degree of occurrence of positive capacity loss of the battery unit based on a specific estimated SOH and a first reference SOH.

[0120] FIG. 7 is a block diagram showing the hardware configuration of a computing system for performing the operation method of a battery diagnostic device according to one embodiment disclosed in this document.

[0121] Referring to FIG. 7, a computing system (200) according to one embodiment disclosed in this document may include an MCU (210), memory (220), an input / output I / F (230), and a communication I / F (240).

[0122] The MCU (210) may be a processor that executes various programs stored in memory (220) (e.g., battery data collection program, graph calculation program, data analysis program, data decomposition algorithm, normalization program, and battery cell diagnosis program, etc.), processes various information including characteristic data of the battery cell, potential variables, etc. through these programs, and performs the functions of the battery diagnosis device (100) shown in FIGS. 1 to 6.

[0123] The memory (220) can store various programs such as a battery data collection program, a graph generation program, a data analysis program, a data decomposition algorithm, a normalization program, and a battery cell diagnosis program.

[0124] These memories (220) may be provided in multiple quantities as needed. The memories (220) may be volatile memories or non-volatile memories. As volatile memories, the memory (220) may use RAM, DRAM, SRAM, etc. As non-volatile memories, the memory (220) may use ROM, PROM, EAROM, EPROM, EEPROM, flash memory, etc. The examples of the memories (220) listed above are merely examples and are not limited to these examples.

[0125] The input / output I / F (230) 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 (210).

[0126] The communication I / F (240) is configured to transmit and receive various data with a server and may be various devices capable of supporting wired or wireless communication. For example, the battery diagnostic device (100) can transmit and receive various information, including battery status data, from a separately provided external server through the communication I / F (240).

[0127] In this way, a computer program according to one embodiment disclosed in this document may be implemented as a module that performs, for example, the functions illustrated in FIG. 2, by being written to memory (220) and processed by an MCU (210).

[0128] In the foregoing, although all components constituting the embodiments disclosed in this document have been described as being combined or operating in combination, the embodiments disclosed in this document are not necessarily limited to such embodiments. That is, within the scope of the purposes of the embodiments disclosed in this document, all components may be selectively combined in one or more ways to operate.

[0129] Furthermore, terms such as "include," "compose," or "have" as described above, unless specifically stated otherwise, mean that the relevant component may be inherent; thus, they should be interpreted as allowing for the inclusion of additional components rather than excluding them. All terms, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which the embodiments disclosed in this document pertain, unless otherwise defined. Commonly used terms, such as those defined in advance, should be interpreted in accordance with their meaning in the context of the relevant technology and, unless explicitly defined in this document, should not be interpreted in an ideal or overly formal sense.

[0130] The foregoing disclosure outlines the features of several embodiments to enable those skilled in the art to better understand aspects of the present disclosure. Those skilled in the art will understand that the present disclosure can be readily used as a basis for designing or modifying other structures to perform the same purpose or achieve the same advantages as the embodiments introduced herein. Furthermore, those skilled in the art will recognize that such equivalent configurations do not depart from the scope of the present disclosure and that various changes, substitutions, and modifications may be made in the present disclosure without departing from the scope of the present disclosure.

[0131] [Explanation of the symbol]

[0132] 1: Battery pack

[0133] 2: Higher-level controller

[0134] 10: Battery unit

[0135] 12: Upper battery unit

[0136] 14: Sensor section

[0137] 16: Switching section

[0138] 20: BMS

[0139] 100: Battery Diagnostic Device

[0140] 110: Interface

[0141] 120: One or more processors

[0142] 200: Computing System

[0143] 210: MCU

[0144] 220: Memory

[0145] 230: Input / Output I / F

[0146] 240: Communication I / F

Claims

1. An interface for acquiring multiple OCV (Open Circuit Voltage) data for a battery unit; and A battery diagnostic device comprising one or more processors that acquire a plurality of estimated State of Charge (SOC) corresponding to at least some of the above OCV data, acquire a plurality of estimated State of Health (SOH) corresponding to at least some of the above estimated SOCs, and diagnose the degree of occurrence of positive capacity loss of the battery unit based on a specific estimated SOH that satisfies a critical SOH condition among the above estimated SOHs.

2. In Claim 1, The above one or more processors, Obtain at least one first estimated SOC included in the first SOC interval among the above estimated SOCs, and Obtaining the specific estimated SOH that satisfies the threshold SOH condition among at least one first estimated SOH corresponding to the first estimated SOC, and A battery diagnostic device that diagnoses the degree of occurrence of positive capacity loss of the battery unit based on the above-mentioned specific estimated SOH.

3. In Claim 2, The above one or more processors, A battery diagnostic device that diagnoses the degree of occurrence of positive capacity loss of the battery unit based on the above-mentioned specific estimated SOH and the first reference SOH.

4. In Claim 2, The above specific estimated SOH is a battery diagnostic device having the maximum value among the above first estimated SOHs.

5. In Claim 1, The above one or more processors, A battery diagnostic device that obtains a plurality of estimated SOHs by performing a process for at least some of the plurality of estimated SOCs, wherein (i) a k-th estimated SOC among the plurality of estimated SOCs, (ii) a k-th charge amount or a k-th discharge amount corresponding to the k-th estimated SOC, and (iii) a k-th estimated SOH corresponding to the k-th estimated SOC based on a (k+1)-th estimated SOC which is the result of charging the battery unit corresponding to the k-th estimated SOC by the k-th charge amount or discharging it by the k-th discharge amount.

6. In Claim 1, The above one or more processors, A battery diagnostic device that obtains a plurality of estimated SOCs corresponding to at least some of the OCV data based on an OCV-SOC table corresponding to a reference battery unit.

7. In Claim 1, The above one or more processors, A battery diagnostic device that obtains the estimated SOH corresponding to the estimated SOC based on the current integration method.

8. In Claim 1, A battery diagnostic device wherein the plurality of OCV data are specific OCV data corresponding to a driving range greater than or equal to a first driving distance and less than a second driving distance among the OCV data corresponding to the driving distance of a mobile body equipped with the battery unit.

9. In Claim 1, The above interface is, A battery diagnostic device that acquires the OCV data in real time from a mobile body equipped with the battery unit.

10. Operation of acquiring multiple OCV (Open Circuit Voltage) data for a battery unit; An operation to acquire a plurality of estimated State of Charge (SOC) corresponding to at least some of the above OCV data; The operation of obtaining a plurality of estimated State of Health (SOH) corresponding to at least some of the plurality of estimated State of Health (SOC) above; and A battery diagnostic method comprising diagnosing the degree of occurrence of positive capacity loss of the battery unit based on a specific estimated SOH that satisfies a critical SOH condition among the estimated SOHs.

11. In Claim 10, The operation of obtaining the above-mentioned plurality of estimated SOCs is, The operation includes obtaining at least one first estimated SOC included in the first SOC interval among the above estimated SOCs, and The operation of obtaining the above plurality of estimated SOHs is, The operation includes obtaining the specific estimated SOH that satisfies the threshold SOH condition among at least one first estimated SOH corresponding to the first estimated SOC, and The operation of diagnosing the degree of occurrence of positive capacity loss of the above battery unit is, A battery diagnostic method comprising diagnosing the degree of occurrence of positive capacity loss of the battery unit based on the above-mentioned specific estimated SOH.

12. In Claim 11, The operation of diagnosing the degree of occurrence of positive capacity loss of the above battery unit is, A battery diagnostic method comprising diagnosing the degree of occurrence of positive capacity loss of the battery unit based on the above-mentioned specific estimated SOH and the first reference SOH.

13. In Claim 10, The operation of obtaining the above plurality of estimated SOHs is, A battery diagnostic method comprising the operation of obtaining a k-th estimated SOH corresponding to the k-th estimated SOC by performing a process for at least some of the plurality of estimated SOCs, wherein the process is based on (i) a k-th estimated SOC among the plurality of estimated SOCs, (ii) a k-th charge amount or a k-th discharge amount corresponding to the k-th estimated SOC, and (iii) a (k+1)-th estimated SOC which is the result of charging the battery unit corresponding to the k-th estimated SOC by the k-th charge amount or discharging by the k-th discharge amount.

14. In Claim 10, The operation of obtaining the above plurality of estimated SOHs is, A battery diagnostic method comprising the operation of obtaining a plurality of estimated SOCs corresponding to at least a portion of the OCV data based on an OCV-SOC table corresponding to a reference battery unit.

15. A computer-readable recording medium having a program that performs the method of any one of paragraphs 10 through 14.

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