Electronic device and battery SOC estimation method therefor

Abstract

An electronic device according to one embodiment of the present disclosure comprises: a memory that stores a plurality of estimation algorithms for estimating the state of charge (SOC) of a battery cell; and a processor operatively connected to the memory, wherein the processor can acquire open circuit voltage (OCV) data of the battery cell, identify, on the basis of the acquired OCV data, any one estimation algorithm from among the plurality of estimation algorithms stored in the memory, and estimate the SOC of the battery cell on the basis of the identified estimation algorithm.

Description

Electronic device and method for estimating its battery SOC

[0001] This application claims the benefit of priority to Republic of Korea Patent Application No. 10-2024-0094928, filed July 18, 2024, the entire contents of which are incorporated herein by reference.

[0002] Embodiments disclosed in this document relate to an electronic device and a method for estimating a battery SOC thereof.

[0003] Recently, research and development on secondary batteries has been actively conducted. Here, secondary batteries are batteries that can be repeatedly charged and discharged, and include both conventional Ni / Cd batteries, Ni / MH batteries, and recent lithium-ion batteries. Among secondary batteries, lithium-ion batteries have the advantage of having a much higher energy density than conventional Ni / Cd and Ni / MH batteries. Furthermore, lithium-ion batteries can be manufactured in a small and lightweight form, so they are used as a power source for mobile devices. Recently, their use has expanded to include power sources for electric vehicles, attracting attention as a next-generation energy storage medium.

[0004] Lithium secondary batteries are generally manufactured by forming an electrode assembly by interposing a separator between a positive electrode including a positive electrode active material including a transition metal oxide containing lithium and a negative electrode including an negative electrode active material capable of storing lithium ions, inserting the electrode assembly into a battery case, injecting a non-aqueous electrolyte that serves as a medium for transferring lithium ions, and then sealing the electrode assembly. The non-aqueous electrolyte generally includes a lithium salt and an organic solvent capable of dissolving the lithium salt.

[0005] Meanwhile, as the applications for these secondary batteries expand, the importance of management systems for more efficient use and management of these batteries is increasing. For example, management systems must be able to accurately estimate the state of charge (SOC) of secondary batteries to appropriately adjust their charge / discharge output and capacity utilization strategies.

[0006] In general, a method of estimating the SOC of a secondary battery is used by using the SOC-OCV relationship, which represents the relationship between the SOC of the secondary battery and the OCV (Open Circuit Voltage). At this time, the SOC-OCV relationship is a unique characteristic determined by the electrode components of the secondary battery, and since the SOC-OCV relationship of some secondary batteries does not change significantly even when degraded, a SOC estimation algorithm based on the SOC-OCV relationship at the BOL (Begin of Life) of the secondary battery is used.

[0007] Meanwhile, battery cells (hereinafter referred to as "manganese-rich cells") containing lithium manganese-rich oxide as a cathode active material are being developed to reduce the manufacturing cost of batteries for electric vehicles. While lithium manganese-rich oxide offers the advantages of lower cost and superior stability compared to conventional lithium nickel-based cathode active materials, it suffers from the problem that existing SOC estimation algorithms are difficult to use because the SOC-OCV relationship changes with deterioration.

[0008] Therefore, it is necessary to understand why the SOC-OCV relationship of manganese-rich cells changes with degeneration and to reflect this in the SOC estimation algorithm.

[0009] According to one embodiment of the present disclosure, an electronic device and a SOC estimation method thereof can be provided, which can identify an estimation algorithm suitable for a current OCV value of a battery cell among a plurality of estimation algorithms based on OCV data of a battery cell, and estimate the SOC of the battery cell based on the identified estimation algorithm.

[0010] The technical problems to be solved by the embodiments of the present disclosure are not limited to the technical problems described above, and other technical problems can be inferred from the following embodiments.

[0011] An electronic device according to one embodiment of the present disclosure includes a memory storing a plurality of estimation algorithms for estimating a State of Charge (SOC) of a battery cell, and a processor operatively connected to the memory, wherein the processor is configured to obtain Open Circuit Voltage (OCV) data of the battery cell, identify one of the plurality of estimation algorithms stored in the memory based on the obtained OCV data, and estimate the SOC of the battery cell based on the identified estimation algorithm.

[0012] In an electronic device according to an embodiment of the present disclosure, the plurality of estimation algorithms include a first estimation algorithm and a second estimation algorithm, and the processor identifies an OCV range in which the OCV value of the battery cell is included based on the acquired OCV data, and when the OCV value of the battery cell is included in the first OCV range, identifies the first estimation algorithm among the plurality of estimation algorithms, and when the OCV value of the battery cell is included in the second OCV range, identifies the second estimation algorithm among the plurality of estimation algorithms.

[0013] In an electronic device according to one embodiment of the present disclosure, the processor can directly obtain the OCV data measured through a sensor or obtain the OCV data through communication from an external device.

[0014] In an electronic device according to an embodiment of the present disclosure, when the first estimation algorithm among the plurality of estimation algorithms is identified, the processor may estimate the SOC of the battery cell based on first SOC-OCV relationship information corresponding to the first OCV range, and when the second estimation algorithm among the plurality of estimation algorithms is identified, the processor may estimate the SOC of the battery cell based on second SOC-OCV relationship information corresponding to the second OCV range.

[0015] In an electronic device according to an embodiment of the present disclosure, when the first estimation algorithm is identified among the plurality of estimation algorithms, the processor estimates a first SOC corresponding to the first OCV range based on the first SOC-OCV relationship information, estimates an SOC of the battery cell corresponding to the entire OCV range composed of the first OCV range and the second OCV range based on the first SOC, and when the second estimation algorithm is identified among the plurality of estimation algorithms, estimates a second SOC corresponding to the second OCV range based on the second SOC-OCV relationship information, and estimates an SOC of the battery cell corresponding to the entire OCV range composed of the first OCV range and the second OCV range based on the second SOC.

[0016] In an electronic device according to an embodiment of the present disclosure, the first OCV range may be a range greater than or equal to a specified OCV value, and the second OCV range may be a range less than or equal to the specified OCV value.

[0017] In an electronic device according to one embodiment of the present disclosure, the specified OCV value may be about 3.2 V.

[0018] In an electronic device according to an embodiment of the present disclosure, when the first estimation algorithm is identified among the plurality of estimation algorithms, the processor estimates the first SOC by performing an extended Kalman filter operation based on the first SOC-OCV relationship information and the OCV value of the battery cell, multiplies the first SOC by a first reference capacity corresponding to the first OCV range, calculates a charging capacity based on the specified OCV value, and divides the sum of the second reference capacity corresponding to the second OCV range and the charging capacity by the sum of the first reference capacity and the second reference capacity to estimate the SOC of the battery cell.

[0019] In an electronic device according to one embodiment of the present disclosure, the battery cell may include a lithium manganese-rich oxide as a positive electrode active material, and the first SOC-OCV relationship information may be information indicating a relationship between an SOC and an OCV of a lithium nickel cobalt manganese oxide, which is a part of the lithium manganese-rich oxide, in the first OCV range.

[0020] In an electronic device according to an embodiment of the present disclosure, when the second estimation algorithm is identified among the plurality of estimation algorithms, the processor estimates the second SOC by performing an extended Kalman filter operation based on the second SOC-OCV relationship information and the OCV value of the battery cell, calculates a first DoD (Depth of Discharge) corresponding to the second OCV range based on the second SOC, multiplies the first DoD by a second reference capacity corresponding to the second OCV range to calculate a discharge capacity based on the specified OCV value, divides the sum of the first reference capacity corresponding to the first OCV range and the discharge capacity by the sum of the first reference capacity and the second reference capacity to calculate a second DoD of the battery cell corresponding to the entire OCV range of the battery cell, and estimates the SOC of the battery cell based on the second DoD.

[0021] In an electronic device according to one embodiment of the present disclosure, the battery cell may include a lithium manganese-rich oxide as a cathode active material, and the second SOC-OCV relationship information may be information indicating a relationship between an SOC and an OCV of a lithium manganese oxide, which is a part of the lithium manganese-rich oxide, in the second OCV range.

[0022] A method for estimating SOC of a battery cell performed by an electronic device according to an embodiment of the present disclosure may include an operation of acquiring OCV (Open Circuit Voltage) data of the battery cell, an operation of identifying one of a plurality of estimation algorithms based on the acquired OCV data, and an operation of estimating SOC of the battery cell based on the identified estimation algorithm.

[0023] In a method for estimating SOC of a battery cell performed by an electronic device according to an embodiment of the present disclosure, the operation of acquiring the OCV data may include an operation of directly acquiring the OCV data measured through a sensor or acquiring the OCV data through communication from an external device.

[0024] In a method for estimating SOC of a battery cell performed by an electronic device according to an embodiment of the present disclosure, the plurality of estimation algorithms may include a first estimation algorithm and a second estimation algorithm, and an operation of identifying any one of the plurality of estimation algorithms may include an operation of identifying an OCV range in which an OCV value of the battery cell is included based on the acquired OCV data, an operation of identifying the first estimation algorithm among the plurality of estimation algorithms when the OCV value of the battery cell is included in the first OCV range, and an operation of identifying the second estimation algorithm among the plurality of estimation algorithms when the OCV value of the battery cell is included in the second OCV range.

[0025] In a method for estimating a SOC of a battery cell performed by an electronic device according to an embodiment of the present disclosure, the operation of estimating the SOC of the battery cell may include, when the first estimation algorithm is identified among the plurality of estimation algorithms, an operation of estimating a first SOC corresponding to the first OCV range based on the first SOC-OCV relationship information, and an operation of estimating the SOC of the battery cell corresponding to the entire OCV range composed of the first OCV range and the second OCV range based on the first SOC, and when the second estimation algorithm is identified among the plurality of estimation algorithms, an operation of estimating a second SOC corresponding to the second OCV range based on the second SOC-OCV relationship information, and an operation of estimating the SOC of the battery cell corresponding to the entire OCV range composed of the first OCV range and the second OCV range based on the second SOC.

[0026] In a method for estimating SOC of a battery cell performed by an electronic device according to an embodiment of the present disclosure, the first OCV range may be a range greater than or equal to a specified OCV value, and the second OCV range may be a range less than or equal to the specified OCV value.

[0027] In a method for estimating SOC of a battery cell performed by an electronic device according to an embodiment of the present disclosure, the specified OCV value may be about 3.2 V.

[0028] In a method for estimating an SOC of a battery cell performed by an electronic device according to an embodiment of the present disclosure, the operation of estimating the SOC of the battery cell may include, when the first estimation algorithm is identified among the plurality of estimation algorithms, estimating the first SOC by performing an extended Kalman filter operation based on the first SOC-OCV relationship information and the OCV value of the battery cell, an operation of multiplying the first SOC by a first reference capacity corresponding to the first OCV range to calculate a charging capacity based on the specified OCV value, and an operation of estimating the SOC of the battery cell by dividing a value obtained by adding the charging capacity and a second reference capacity corresponding to the second OCV range by a value obtained by adding the first reference capacity and the second reference capacity.

[0029] In a method for estimating an SOC of a battery cell performed by an electronic device according to an embodiment of the present disclosure, the operation of estimating the SOC of the battery cell includes: an operation of estimating the second SOC by performing an extended Kalman filter operation based on the second SOC-OCV relationship information and the OCV value of the battery cell when the second estimation algorithm is identified among the plurality of estimation algorithms; an operation of calculating a first DoD (Depth of Discharge) corresponding to the second OCV range based on the second SOC; an operation of calculating a discharge capacity based on the designated OCV value by multiplying the first DoD by a second reference capacity corresponding to the second OCV range; an operation of calculating a second DoD of the battery cell corresponding to the entire OCV range of the battery cell by dividing a value obtained by adding the first reference capacity corresponding to the first OCV range and the discharge capacity by a value obtained by adding the first reference capacity and the second reference capacity; and an operation of estimating the SOC of the battery cell based on the second DoD. It may include actions that are being estimated.

[0030] According to the embodiments disclosed in this document, the accuracy of SOC estimation can be improved by applying a SOC estimation algorithm that takes into account the characteristics of a manganese-rich cell.

[0031] The effects of the invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description of the claims.

[0032] Figure 1 shows a graph showing OCV according to SOC at each of BOL (Begin of Life) and MOL (Middle of Life) of a manganese-rich cell.

[0033] Figure 2 shows a graph showing the capacity according to each OCV range in each SOHC and manganese-rich cell BOL and MOL according to each OCV range of the manganese-rich cell.

[0034] Figure 3a shows a graph showing OCV according to SOC in the first OCV range of a manganese-rich cell.

[0035] Figure 3b shows a graph showing OCV according to SOC in the second OCV range of the manganese-rich cell.

[0036] FIG. 4 is a block diagram of an electronic device according to an embodiment of the present disclosure.

[0037] FIG. 5 is a diagram illustrating an example of an electronic device estimating the SOC of a battery cell based on a first estimation algorithm according to an embodiment of the present disclosure.

[0038] FIG. 6 is a diagram illustrating an example of an electronic device estimating the SOC of a battery cell based on a second estimation algorithm according to an embodiment of the present disclosure.

[0039] FIG. 7 is a flowchart of the operation of an electronic device according to an embodiment of the present disclosure.

[0040] FIG. 8 is a flowchart of the operation of an electronic device according to an embodiment of the present disclosure.

[0041] In describing the embodiments, descriptions of technical details that are well known in the technical field to which the present disclosure pertains and are not directly related to the present disclosure will be omitted. This is to avoid obscuring the gist of the present disclosure by omitting unnecessary explanations and to convey the gist more clearly.

[0042] For the same reason, some components in the attached drawings are exaggerated, omitted, or schematically depicted. Furthermore, the dimensions of each component do not entirely reflect its actual size. Identical or corresponding components in each drawing are assigned the same reference numbers.

[0043] The advantages and features of the present disclosure, and methods for achieving them, will become clearer with reference to the embodiments described in detail below together with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below and may be implemented in various different forms. These embodiments are provided solely to ensure that the disclosure of the present disclosure is complete and to fully inform those skilled in the art of the scope of the invention, and the present disclosure is defined only by the scope of the claims. Like reference numerals refer to like elements throughout the specification.

[0044] At this time, it will be understood that each block of the processing flowchart drawings and combinations of the flowchart drawings can be performed by computer program instructions. These computer program instructions can be loaded into a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing equipment, so that the instructions executed by the processor of the computer or other programmable data processing equipment create a means for performing the functions described in the flowchart block(s). These computer program instructions can also be stored in a computer-available or computer-readable memory that can be directed to a computer or other programmable data processing equipment to implement the functions in a specific manner, so that the instructions stored in the computer-available or computer-readable memory can produce an article of manufacture that includes a command means for performing the functions described in the flowchart block(s). The computer program instructions can also be loaded onto a computer or other programmable data processing equipment, so that a series of operation steps are performed on the computer or other programmable data processing equipment to create a computer-executable process, so that the instructions that execute the computer or other programmable data processing equipment can provide steps for performing the functions described in the flowchart block(s).

[0045] Additionally, each block may represent a module, segment, or portion of code that contains one or more executable instructions for performing a specific logical function(s). It should also be noted that in some alternative implementation examples, the functions described in the blocks may occur out of order. For example, two blocks depicted in succession may actually be executed substantially concurrently, or the blocks may sometimes be executed in reverse order, depending on their respective functions.

[0046] Here, the term '~ unit' used in the present embodiment means software or hardware components such as FPGA (Field Programmable Gate Array) or ASIC (Application-Specific Integrated Circuit), and the '~ unit' performs certain roles. However, the '~ unit' is not limited to software or hardware. The '~ unit' may be configured to be on an addressable storage medium or may be configured to play one or more processors. Therefore, for example, the '~ unit' includes components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functions provided within the components and '~ units' may be combined into a smaller number of components and '~ units' or further separated into additional components and '~ units'. Additionally, components and '~parts' may be implemented to regenerate one or more CPUs within a device or secure multimedia card.

[0047] The expression "at least one of a, b, and c" described throughout the specification may encompass 'a alone', 'b alone', 'c alone', 'a and b', 'a and c', 'b and c', or 'all of a, b, and c'.

[0048] The "terminal" mentioned below may be implemented as a computer or portable terminal that can connect to a server or other terminal via a network. Here, the computer includes, for example, a notebook, desktop, laptop, etc. equipped with a web browser, and the portable terminal may include, for example, a wireless communication device that guarantees portability and mobility, and may include all types of handheld-based wireless communication devices such as communication-based terminals such as IMT (International Mobile Telecommunication), CDMA (Code Division Multiple Access), W-CDMA (W-Code Division Multiple Access), LTE (Long Term Evolution), smartphones, tablet PCs, etc.

[0049] Below, embodiments of the present disclosure are described in detail with reference to the attached drawings so that those skilled in the art can easily implement the present disclosure. However, the present disclosure may be implemented in various different forms and is not limited to the embodiments described herein.

[0050] Hereinafter, the characteristics of the manganese-rich cell will be described with reference to FIGS. 1, 2, 3a, and 3b, and an embodiment of the present disclosure will be described in detail with reference to FIGS. 4 to 8.

[0051] Figure 1 shows a graph (100) showing OCV according to SOC at each of BOL (Begin of Life) and MOL (Middle of Life) of a manganese-rich cell. Here, the manganese-rich cell may be a battery cell including a lithium manganese-rich oxide as a cathode active material according to one embodiment. For example, the lithium manganese-rich oxide may include lithium manganese oxide (e.g., Li2MnO3) and lithium nickel cobalt manganese oxide (e.g., NCM).

[0052] Referring to the graph (100) of Fig. 1, it can be confirmed that the SOC-OCV relationship of the manganese-rich cell is different in BOL and MOL. This difference may be caused by the OCV Decay phenomenon of the manganese-rich cell as the secondary battery is repeatedly charged and discharged. The lithium manganese-rich oxide contained in the manganese-rich cell generates manganese oxide (e.g., MnO2) due to a phase change according to the charge and discharge. The generated manganese oxide increases the capacity of the manganese-rich cell by participating in the redox reaction. This may be one of the causes of the OCV Decay phenomenon in the manganese-rich cell.

[0053] Figure 2 shows a graph (200) showing the capacity according to each OCV range in each SOHC and manganese-rich cell BOL and MOL according to each OCV range of the manganese-rich cell.

[0054] In the graph (200) of Fig. 2, the MOL section capacity and BOL section capacity represent the expressed capacity in the corresponding OCV range (e.g., 3 V to 3.1 V range, 3.1 V to 3.2 V range, etc.) in the MOL and BOL of the manganese-rich cell. In addition, the section-specific SOHC represents the SOH (State of Health) for the capacity in the corresponding OCV range of the manganese-rich cell, and is the value obtained by dividing the MOL section capacity in the corresponding OCV range by the BOL section capacity.

[0055] Referring to graph (200), it can be seen that, based on the point where the OCV of the manganese-rich cell becomes 3.2 V, the MOL section capacity is greater than the BOL section capacity in the OCV ranges before that point (e.g., 3 V to 3.1 V range, 3.1 V to 3.2 V range), whereas, in the OCV ranges thereafter (e.g., 3.2 V to 3.3 V range, 3.3 V to 3.4 V range, etc.), the BOL section capacity is greater than the MOL section capacity. Accordingly, it can be seen that the SOHC of the manganese-rich cell is higher than 1 in the OCV range of 3.2 V or less, but lower than 1 in the OCV range of 3.2 V or more. For example, a manganese-rich cell can be understood to have increased capacity at OCVs below 3.2 V where the SOHC is higher than 1, but decreased capacity at OCVs above 3.2 V where the SOHC is lower than 1.

[0056] Based on these data, it can be assumed that the SOC-OCV relationship of manganese-rich cells can change around a certain OCV value (e.g., 3.2 V).

[0057] Fig. 3a shows a graph (310) showing OCV according to SOC in a first OCV range (e.g., 3.2 V to 4.35 V) of a manganese-rich cell. Fig. 3b shows a graph (320) showing OCV according to SOC in a second OCV range (e.g., 2.5 V to 3.2 V) of a manganese-rich cell. The X-axis of the graph (310) represents the SOC of the manganese-rich cell in the first OCV range, scaled from 0% to 100%. In addition, the X-axis of the graph (320) represents the SOC of the manganese-rich cell in the second OCV range, scaled from 0% to 100%.

[0058] Referring to the graph (310) of FIG. 3a and the graph (320) of FIG. 3b, when the range above the OCV value of 3.2 V is set as the first OCV range and the range below it is set as the second OCV range, it can be confirmed that the SOC-OCV relationship in each OCV range is the same in BOL and MOL. For example, it can be understood that the SOC-OCV relationship of a manganese-rich cell changes based on the OCV of 3.2 V.

[0059] Accordingly, when estimating the SOC of a manganese-rich cell, if the SOC-OCV relationship corresponding to the first OCV range is used in the first OCV range above a specific OCV (e.g., 3.2 V), and the SOC-OCV relationship corresponding to the second OCV range is used in the second OCV range below a specific OCV (e.g., 3.2 V), accurate SOC estimation may be possible.

[0060] In the above, it has been described that the OCV value at which the SOC-OCV relationship of the manganese-rich cell changes is approximately 3.2 V, but is not limited thereto, and the OCV value at which the SOC-OCV relationship of the manganese-rich cell changes may vary depending on, for example, the components of the manganese-rich cell.

[0061] FIG. 4 is a block diagram of an electronic device (400) according to one embodiment of the present disclosure.

[0062] According to one embodiment, the electronic device (400) may include a communication circuit (410), a sensor (420), a memory (430), and / or a processor (440). According to an embodiment, the electronic device (400) illustrated in FIG. 4 may further include at least one component (e.g., a display, an input device, or an output device) other than the components illustrated in FIG. 4.

[0063] According to one embodiment, the electronic device (400) may be implemented as a battery management system (BMS) that is placed in a battery pack and manages and controls the status of battery cells included in the battery pack. According to another embodiment, the electronic device (400) may be implemented as at least one of a notebook, desktop, laptop, and server computing device that receives data on battery cells from an external electronic device and estimates SOC.

[0064] According to one embodiment, the communication circuit (410) can establish a wired communication channel and / or a wireless communication channel between the electronic device (400) and an external electronic device and / or an external server, and transmit and receive data with the external electronic device and / or the external server including the battery cell through the established communication channel. According to one embodiment, the communication circuit (410) can receive OCV data of the battery cell from the external electronic device and / or the external server.

[0065] Here, communication, i.e., transmission and reception of data, can be performed wired or wirelessly. To this end, the communication circuit (310) may include a wired communication module that connects to the Internet, etc., via a LAN (Local Area Network), a mobile communication module that connects to a mobile communication network via a mobile communication base station and transmits and receives data, a short-range communication module that uses a WLAN (Wireless Local Area Network) series communication method such as Wi-Fi or a WPAN (Wireless Personal Area Network) series communication method such as Bluetooth or Zigbee, a satellite communication module that uses a GNSS (Global Navigation Satellite System) such as a GPS (Global Positioning System), or a combination thereof.

[0066] According to one embodiment, the sensor (420) can measure values ​​related to the state of a battery cell. According to one embodiment, the values ​​related to the state can include at least one of a voltage value, a current value, and a temperature value of the battery cell.

[0067] According to one embodiment, one of the communication circuit (410) and the sensor (420) may be omitted in the electronic device (400). For example, if the electronic device (400) is implemented as a BMS, the electronic device (400) can obtain OCV data by calculating OCV based on values ​​related to the state of the battery cell measured through the sensor (420), and thus the communication circuit (410) may be omitted. As another example, if the electronic device (400) is implemented as a computing device (e.g., a server) that receives data of a battery cell from an external electronic device, the sensor (420) may be omitted because the electronic device (400) can obtain OCV data of the battery cell through the communication circuit (410).

[0068] According to one embodiment, the memory (430) may include volatile memory and / or non-volatile memory.

[0069] According to one embodiment, the memory (430) may store data used by at least one component (e.g., the processor (440)) of the electronic device (400). For example, the data may include software (or instructions related thereto), input data, or output data. In one embodiment, the instructions, when executed by the processor (440), may cause the electronic device (400) to perform operations defined by the instructions.

[0070] According to one embodiment, the memory (430) can store a plurality of estimation algorithms for estimating the SOC of a battery cell.

[0071] According to one embodiment, the processor (440) may be implemented as a computer or similar device according to hardware, software, or a combination thereof. In terms of hardware, the processor (440) may be implemented in the form of an electronic circuit that processes electrical signals to perform a control function, and in terms of software, the processor (440) may be implemented in the form of a program that drives the hardware processor (440). According to one embodiment, the processor (440) may include a central processing unit, an application processor, a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor.

[0072] Meanwhile, unless otherwise specifically stated in the following description, the operation of the electronic device (400) may be interpreted as being performed under the control of the processor (440).

[0073] Hereinafter, a method for an electronic device (400) to estimate the SOC of a battery cell is described. Hereinafter, the battery cell may be a manganese-rich cell.

[0074] According to one embodiment, the electronic device (400) can obtain OCV data of a battery cell. For example, the OCV data may be time series data indicating past and present OCV values ​​of the battery cell. As described above, for example, when the electronic device (400) is implemented as a BMS, the electronic device (400) can obtain OCV data by calculating OCV based on values ​​related to the state of the battery cell measured through the sensor (420). Alternatively, when the electronic device (400) is implemented as a computing device (e.g., a server) that receives data of the battery cell from an external electronic device, the electronic device (400) can obtain OCV data of the battery cell through the communication circuit (410).

[0075] According to one embodiment, the electronic device (400) can identify one of a plurality of estimation algorithms stored in the memory (430) based on the OCV data of the battery cell. According to one embodiment, the electronic device (400) can identify an estimation algorithm to be used for estimating the SOC of the battery cell among the plurality of estimation algorithms based on the OCV data of the battery cell. For example, the electronic device (400) can identify an estimation algorithm corresponding to an OCV range within which the OCV value of the battery cell is included.

[0076] Here, the plurality of estimation algorithms may include a first estimation algorithm and a second estimation algorithm. Additionally, the first estimation algorithm and the second estimation algorithm may correspond to a first OCV range and a second OCV range, respectively.

[0077] According to one embodiment, the electronic device (400) can identify an OCV range in which the OCV value of the battery cell is included based on the OCV data. Here, the entire OCV range of the battery cell can include a first OCV range and a second OCV range. For example, the first OCV range can be a range that is equal to or greater than a specified OCV value (e.g., 3.2 V), and the second OCV range can be a range that is less than the specified OCV value (e.g., 3.2 V). The electronic device (400) can identify an OCV range in which the OCV value of the battery cell is included among the first OCV range and the second OCV range.

[0078] According to one embodiment, the electronic device (400) may identify an estimation algorithm corresponding to an OCV range in which the OCV value of the battery cell is included among a plurality of estimation algorithms. For example, if the OCV value of the battery cell is included in a first OCV range (e.g., a range equal to or greater than 3.2 V), the electronic device (400) may identify a first estimation algorithm among the plurality of estimation algorithms. As another example, if the OCV value of the battery cell is included in a second OCV range (e.g., a range equal to or less than 3.2 V), the electronic device (400) may identify a second estimation algorithm among the plurality of estimation algorithms.

[0079] According to one embodiment, the electronic device (400) can estimate the SOC of a battery cell based on an identified estimation algorithm among a plurality of estimation algorithms.

[0080] Hereinafter, with reference to FIGS. 5 and 6, a method for an electronic device (400) to estimate the SOC of a battery cell based on a first estimation algorithm and a second estimation algorithm will be described. The description of FIG. 5 below relates to the first estimation algorithm, and the description of FIG. 6 relates to the second estimation algorithm.

[0081] FIG. 5 is a diagram for explaining an example in which an electronic device (400) according to one embodiment of the present disclosure estimates the SOC of a battery cell based on a first estimation algorithm.

[0082] Referring to FIG. 5, the electronic device (400) estimates a first SOC (510) corresponding to a first OCV range, and based on the estimated first SOC (510), the first reference capacity (520), the charge capacity (530), and the second reference capacity (540), can estimate an SOC (550) corresponding to the entire OCV range composed of the first OCV range and the second OCV range.

[0083] According to one embodiment, the electronic device (400) can estimate the SOC (550) corresponding to the entire OCV range of the battery cell based on first SOC-OCV relationship information corresponding to the first OCV range. Here, the first SOC-OCV relationship information may be information indicating a relationship between the SOC and the OCV in the first OCV range of lithium nickel cobalt manganese oxide, which is a part of the lithium manganese-rich oxide. For example, the first SOC-OCV relationship information may be a lookup table indicating the SOC corresponding to the OCV value in the first OCV range.

[0084] According to one embodiment, the electronic device (400) can estimate a first SOC (510) corresponding to a first OCV range based on first SOC-OCV relationship information obtained from a lookup table. Here, the first SOC (510) can be a scaled range of 0% to 100% in the first OCV range. For example, the first SOC (510) can be understood as representing an SOC in the first OCV range, rather than representing the entire SOC of the battery cell. For example, the electronic device (400) can estimate the first SOC (510) by performing an Extended Kalman Filter operation based on the first SOC-OCV relationship information obtained from the lookup table and an OCV value of a battery cell corresponding to a specific OCV.

[0085] According to one embodiment, the electronic device (400) can calculate a charge capacity (530) based on a specified OCV value (e.g., 3.2 V) by multiplying a first SOC (510) and a first reference capacity (520). Here, the first reference capacity (520) may correspond to a first OCV range. For example, the first reference capacity (520) may be a capacity (e.g., 80 Ah) obtained by subtracting a capacity (e.g., 20 Ah) at a specified OCV value (e.g., 3.2 V) from the total capacity of the battery cell (e.g., 100 Ah). Additionally, the charge capacity (530) may be a capacity required for charging from the specified OCV value to the OCV value of the current battery cell.

[0086] According to one embodiment, the electronic device (400) can calculate the charge capacity (530) based on the following mathematical expression 1.

[0087]

[0088] According to one embodiment, the electronic device (400) can estimate the SOC (550) of the battery cell by dividing the sum of the second reference capacity (540) and the charge capacity (530) by the sum of the first reference capacity (520) and the second reference capacity (540). Here, the second reference capacity (540) may correspond to a second OCV range. For example, the second reference capacity (540) may be a capacity (e.g., 20 Ah) at a specified OCV value (e.g., 3.2 V) of the battery cell.

[0089] According to one embodiment, the electronic device (400) can calculate the SOC (550) corresponding to the entire OCV range of the battery cell based on the following mathematical expression 2.

[0090]

[0091] FIG. 6 is a diagram illustrating an example of an electronic device (400) estimating the SOC of a battery cell based on a second estimation algorithm according to an embodiment of the present disclosure.

[0092] Referring to FIG. 6, the electronic device (400) estimates a second SOC (610) corresponding to the second OCV range, and based on the estimated second SOC (610), the first reference capacity (520), the second reference capacity (540), and the discharge capacity (620), can estimate an SOC (630) corresponding to the entire OCV range composed of the first OCV range and the second OCV range.

[0093] According to one embodiment, the electronic device (400) can estimate the SOC (630) corresponding to the entire OCV range of the battery cell based on second SOC-OCV relationship information corresponding to the second OCV range. Here, the second SOC-OCV relationship information may be information indicating a relationship between the SOC and the OCV of a lithium manganese oxide, which is a part of the lithium manganese-rich oxide, in the second OCV range. For example, the second SOC-OCV relationship information may be a lookup table indicating the SOC corresponding to the OCV value in the second OCV range.

[0094] According to one embodiment, the electronic device (400) can estimate a second SOC (610) corresponding to a second OCV range based on second SOC-OCV relationship information obtained from a lookup table. Here, the second SOC (610) can be a scaled range of 0% to 100% in the second OCV range. For example, the second SOC (610) can be understood as representing an SOC in the second OCV range, rather than representing the entire SOC of the battery cell. For example, the electronic device (400) can estimate the second SOC (610) by performing an extended Kalman filter operation based on the second SOC-OCV relationship information obtained from the lookup table and an OCV value of a battery cell corresponding to a specific OCV.

[0095] According to one embodiment, the electronic device (400) can calculate a first Depth of Discharge (DoD) corresponding to a second OCV range based on the second SOC (610). For example, the electronic device (400) can calculate the first DoD based on a specified operation (e.g., 100 - the second SOC).

[0096] According to one embodiment, the electronic device (400) can calculate a discharge capacity (620) based on a specified OCV value (e.g., 3.2 V) by multiplying the first DoD and the second reference capacity (540). Here, the discharge capacity (620) can be a discharged capacity from the specified OCV value (e.g., 3.2 V) to the OCV value of the current battery cell.

[0097] According to one embodiment, the electronic device (400) can calculate the discharge capacity (620) based on the following mathematical expression 3.

[0098]

[0099] According to one embodiment, the electronic device (400) may calculate the second DoD of the battery cell by dividing the sum of the first reference capacity (520) and the discharge capacity (620) by the sum of the first reference capacity (520) and the second reference capacity (540). Here, the second DoD may correspond to the entire OCV range of the battery cell.

[0100] According to one embodiment, the electronic device (400) can calculate the second DoD of the battery cell based on the following mathematical expression 4.

[0101]

[0102] According to one embodiment, the electronic device (400) can calculate the SOC (630) of the battery cell based on the second DoD. For example, the electronic device (400) can calculate the SOC (630) corresponding to the entire OCV range consisting of the first OCV range and the second OCV range based on a specified operation (e.g., 100 - the second DoD).

[0103] FIG. 7 is a flowchart illustrating the operation of an electronic device according to an embodiment of the present disclosure. Since the operation method of FIG. 7 can be performed by the electronic device (400) of FIG. 4, any description overlapping with the above description may be omitted, and the method may be described using the components of FIG. 4.

[0104] The embodiment illustrated in FIG. 7 is only one embodiment, and the order of operations according to various embodiments of the present disclosure may be different from that illustrated in FIG. 7, and some operations illustrated in FIG. 7 may be omitted, the order between operations may be changed, or operations may be merged.

[0105] Referring to FIG. 7, in operation 710, the electronic device (400) may obtain OCV data of a battery cell. For example, the OCV data may be time series data indicating past and present OCV values ​​of the battery cell. As described above, for example, when the electronic device (400) is implemented as a BMS, the electronic device (400) may obtain OCV data by calculating OCV based on values ​​related to the state of the battery cell measured through the sensor (420). Alternatively, when the electronic device (400) is implemented as a computing device (e.g., a server) that receives data of a battery cell from an external electronic device, the electronic device (400) may obtain OCV data of the battery cell through the communication circuit (410).

[0106] In operation 720, the electronic device (400) can identify an estimation algorithm corresponding to an OCV range in which the OCV value of the battery cell is included among a plurality of estimation algorithms stored in the memory (430) based on the OCV data of the battery cell obtained in operation 710.

[0107] At operation 730, the electronic device (400) can estimate the SOC corresponding to the entire OCV range of the battery cell based on the estimation algorithm identified at operation 720.

[0108] The electronic device (400) may be described in more detail with reference to FIG. 8 below regarding operation 720 of identifying one of a plurality of estimation algorithms and operation 730 of estimating an SOC corresponding to the entire OCV range of a battery cell based on the identified estimation algorithm.

[0109] FIG. 8 is a flowchart illustrating the operation of an electronic device according to an embodiment of the present disclosure. Since the operation method of FIG. 8 can be performed by the electronic device (400) of FIG. 4, any description overlapping with the above-described content may be omitted, and the method may be described using the components of FIG. 4.

[0110] The embodiment illustrated in FIG. 8 is only one embodiment, and the order of operations according to various embodiments of the present disclosure may be different from that illustrated in FIG. 8, and some operations illustrated in FIG. 8 may be omitted, the order between operations may be changed, or operations may be merged.

[0111] Referring to FIG. 8, in operation 810, the electronic device (400) may identify an OCV range in which the OCV value of the battery cell is included based on the OCV data acquired in operation 710 of FIG. 7. Here, the entire OCV range of the battery cell may include a first OCV range and a second OCV range. For example, the first OCV range may be a range that is equal to or greater than a specified OCV value (e.g., 3.2 V), and the second OCV range may be a range that is less than the specified OCV value. The electronic device (400) may identify an OCV range in which the OCV value of the battery cell is included among the first OCV range and the second OCV range.

[0112] If the OCV value of the battery cell is identified as being within the first OCV range in operation 810, the process branches to operation 820 (operation 810 - first OCV range), and the electronic device (400) can identify a first estimation algorithm among a plurality of estimation algorithms stored in the memory (430).

[0113] In operation 830, the electronic device (400) can estimate a first SOC corresponding to the first OCV range based on first SOC-OCV relationship information corresponding to the first OCV range. Here, the first SOC can range from 0% to 100%. For example, the first SOC can be understood as representing a scaled SOC in the first OCV range, rather than representing the full SOC of the battery cell. For example, the electronic device (400) can estimate the scaled first SOC in the first OCV range by performing an extended Kalman filter operation based on the first SOC-OCV relationship information and the OCV value of the battery cell.

[0114] At operation 840, the electronic device (400) can estimate the SOC of the battery cell corresponding to the entire OCV range based on the first SOC estimated at operation 830.

[0115] According to one embodiment, the electronic device (400) may calculate a charging capacity based on a specified OCV value (e.g., 3.2 V) by multiplying a first SOC and a first reference capacity. Here, the first reference capacity may correspond to a first OCV range. For example, the first reference capacity may be a capacity (e.g., 80 Ah) obtained by subtracting a capacity at a specified OCV value (e.g., 20 Ah) from the total capacity of the battery cell (e.g., 100 Ah). Additionally, the charging capacity may be a capacity required for charging from the specified OCV value to the current OCV value of the battery cell.

[0116] According to one embodiment, the electronic device (400) may estimate the SOC of the battery cell by dividing the sum of the second reference capacity and the charge capacity by the sum of the first reference capacity and the second reference capacity. Here, the second reference capacity may correspond to the second OCV range. For example, the second reference capacity may be the capacity at a specified OCV value of the battery cell (e.g., 20 Ah).

[0117] If the OCV value of the battery cell is identified as being within the second OCV range in operation 810, the process branches to operation 850 (operation 810 - second OCV range), and the electronic device (400) can identify a second estimation algorithm among the plurality of estimation algorithms stored in the memory (430).

[0118] In operation 860, the electronic device (400) can estimate a second SOC corresponding to the second OCV range based on second SOC-OCV relationship information corresponding to the second OCV range. Here, the second SOC can range from 0% to 100%. For example, the second SOC can be understood as representing a scaled SOC in the second OCV range, rather than representing the full SOC of the battery cell. For example, the electronic device (400) can estimate the scaled second SOC in the second OCV range by performing an extended Kalman filter operation based on the second SOC-OCV relationship information and the OCV value of the battery cell.

[0119] At operation 870, the electronic device (400) can estimate the SOC of the battery cell corresponding to the entire OCV range based on the second SOC estimated at operation 860.

[0120] According to one embodiment, the electronic device (400) can calculate a first DoD corresponding to a second OCV range based on a second SOC.

[0121] According to one embodiment, the electronic device (400) may multiply the first DoD and the second reference capacity to calculate a discharge capacity based on a specified OCV value (e.g., 3.2 V). Here, the discharge capacity may be a discharge capacity from the specified OCV value to the OCV value of the current battery cell.

[0122] According to one embodiment, the electronic device (400) may calculate the second DoD of the battery cell by dividing the sum of the first reference capacity and the discharge capacity by the sum of the first reference capacity and the second reference capacity. Here, the second DoD may correspond to the entire OCV range of the battery cell.

[0123] According to one embodiment, the electronic device (400) can calculate the SOC of the battery cell based on the second DoD. For example, the electronic device (400) can calculate the SOC based on a specified operation (e.g., 100 - the second DoD).

[0124] The battery management device according to the above-described embodiments may include a processor, a memory for storing and executing program data, permanent storage such as a disk drive, a communication port for communicating with an external device, a user interface device such as a touch panel, a key, an icon, etc. The methods implemented as software modules or algorithms may be stored on a computer-readable recording medium as computer-readable codes or program commands that can be executed on the processor. Here, the computer-readable recording medium includes a magnetic storage medium (e.g., read-only memory (ROM), random-access memory (RAM), floppy disk, hard disk, etc.) and an optical reading medium (e.g., CD-ROM, DVD: Digital Versatile Disc)). The computer-readable recording medium may be distributed to computer systems connected to a network, so that the computer-readable code can be stored and executed in a distributed manner. The medium is readable by a computer, stored in a memory, and executed by a processor.

[0125] Various embodiments of the present disclosure may be represented by functional block configurations and various processing steps. These functional blocks may be implemented by various hardware and / or software components that perform specific functions. For example, embodiments may employ direct circuit components, such as memory, processing, logic, look-up tables, etc., that may perform various functions under the control of one or more microprocessors or other control devices. Similarly, the present embodiments may be implemented in a programming or scripting language, such as C, C++, Java, or an assembler, including various algorithms implemented as a combination of data structures, processes, routines, or other programming components. Functional aspects may be implemented as algorithms that execute on one or more processors. Furthermore, the present embodiments may employ conventional techniques for electronic configuration, signal processing, and / or data processing. Terms like "mechanism," "element," "means," and "composition" can be used broadly and are not limited to mechanical or physical components. These terms can also encompass a series of software routines, such as those associated with a processor.

[0126] The above-described embodiments are merely examples, and other embodiments may be implemented within the scope of the claims set forth below.

Claims

1. In electronic devices, A memory storing multiple estimation algorithms for estimating the SOC (State of Charge) of a battery cell; and comprising a processor operatively connected to said memory, The above processor, Obtain the OCV (Open Circuit Voltage) data of the above battery cell, Based on the acquired OCV data, identify one of the plurality of estimation algorithms stored in the memory, An electronic device that estimates the SOC of the battery cell based on the identified estimation algorithm.

2. In paragraph 1, The above plural estimation algorithms include a first estimation algorithm and a second estimation algorithm, The above processor, Based on the acquired OCV data, an OCV range including the OCV value of the battery cell is identified, If the OCV value of the battery cell is within the first OCV range, the first estimation algorithm is identified among the plurality of estimation algorithms, An electronic device that identifies the second estimation algorithm among the plurality of estimation algorithms when the OCV value of the battery cell falls within the second OCV range.

3. In paragraph 2, The above processor, When the first estimation algorithm among the plurality of estimation algorithms is identified, the SOC of the battery cell is estimated based on the first SOC-OCV relationship information corresponding to the first OCV range, An electronic device that estimates the SOC of the battery cell based on second SOC-OCV relationship information corresponding to the second OCV range when the second estimation algorithm is identified among the plurality of estimation algorithms.

4. In paragraph 3, The above processor, When the first estimation algorithm is identified among the above multiple estimation algorithms, Estimating a first SOC corresponding to the first OCV range based on the first SOC-OCV relationship information, Estimating the SOC of the battery cell corresponding to the entire OCV range consisting of the first OCV range and the second OCV range based on the first SOC, When the second estimation algorithm is identified among the above multiple estimation algorithms, Estimating a second SOC corresponding to the second OCV range based on the second SOC-OCV relationship information, An electronic device that estimates the SOC of the battery cell corresponding to the entire OCV range consisting of the first OCV range and the second OCV range based on the second SOC.

5. In paragraph 4, The above first OCV range is a range greater than or equal to the specified OCV value, An electronic device wherein the second OCV range is a range less than the specified OCV value.

6. In paragraph 5, The above processor, When the first estimation algorithm is identified among the plurality of estimation algorithms, the first SOC is estimated by performing an extended Kalman filter operation based on the first SOC-OCV relationship information and the OCV value of the battery cell, By multiplying the first reference capacity corresponding to the first SOC and the first OCV range, a charging capacity based on the specified OCV value is calculated, An electronic device that estimates the SOC of the battery cell by dividing the sum of the second reference capacity corresponding to the second OCV range and the charge capacity by the sum of the first reference capacity and the second reference capacity.

7. In paragraph 6, The above battery cell comprises lithium manganese-rich oxide as a cathode active material, An electronic device, wherein the first SOC-OCV relationship information is information indicating a relationship between the SOC and the OCV in the first OCV range of the lithium nickel cobalt manganese oxide, which is part of the lithium manganese-rich oxide.

8. In paragraph 5, The above processor, When the second estimation algorithm is identified among the plurality of estimation algorithms, the second SOC is estimated by performing an extended Kalman filter operation based on the second SOC-OCV relationship information and the OCV value of the battery cell. Based on the second SOC, a first DoD (Depth of Discharge) corresponding to the second OCV range is calculated, By multiplying the first DoD and the second reference capacity corresponding to the second OCV range, a discharge capacity based on the specified OCV value is calculated, The second DoD of the battery cell corresponding to the entire OCV range of the battery cell is calculated by dividing the sum of the first reference capacity and the discharge capacity corresponding to the first OCV range by the sum of the first reference capacity and the second reference capacity, An electronic device for estimating the SOC of the battery cell based on the second DoD.

9. In paragraph 8, The above battery cell comprises lithium manganese-rich oxide as a cathode active material, An electronic device in which the second SOC-OCV relationship information is information indicating a relationship between the SOC and OCV in the second OCV range of lithium manganese oxide, which is part of the lithium manganese-rich oxide.

10. In a method for estimating the SOC of a battery cell performed by an electronic device, An operation of acquiring OCV (Open Circuit Voltage) data of the above battery cell; An operation of identifying one of a plurality of estimation algorithms based on the acquired OCV data; and A SOC estimation method, comprising an operation of estimating the SOC of the battery cell based on the identified estimation algorithm.

11. In paragraph 10, The above plural estimation algorithms include a first estimation algorithm and a second estimation algorithm, The operation of identifying one of the above multiple estimation algorithms comprises: An operation of identifying an OCV range that includes the OCV value of the battery cell based on the acquired OCV data; If the OCV value of the battery cell is included in the first OCV range, an operation of identifying the first estimation algorithm among the plurality of estimation algorithms, and A method for estimating SOC, comprising an operation of identifying the second estimation algorithm among the plurality of estimation algorithms when the OCV value of the battery cell is included in the second OCV range.

12. In paragraph 11, The operation of estimating the SOC of the above battery cell is as follows: When the first estimation algorithm is identified among the above multiple estimation algorithms, An operation of estimating a first SOC corresponding to the first OCV range based on the first SOC-OCV relationship information, and An operation of estimating the SOC of the battery cell corresponding to the entire OCV range consisting of the first OCV range and the second OCV range based on the first SOC, When the second estimation algorithm is identified among the above multiple estimation algorithms, An operation of estimating a second SOC corresponding to the second OCV range based on the second SOC-OCV relationship information, and A SOC estimation method, comprising an operation of estimating the SOC of the battery cell corresponding to the entire OCV range consisting of the first OCV range and the second OCV range based on the second SOC.

13. In paragraph 12, The above first OCV range is a range greater than or equal to the specified OCV value, A method for estimating SOC, wherein the second OCV range is a range less than the specified OCV value.

14. In paragraph 13, The operation of estimating the SOC of the above battery cell is as follows: When the first estimation algorithm is identified among the plurality of estimation algorithms, an operation of estimating the first SOC by performing an extended Kalman filter operation based on the first SOC-OCV relationship information and the OCV value of the battery cell; An operation of calculating a charging capacity based on the specified OCV value by multiplying the first reference capacity corresponding to the first SOC and the first OCV range, and A method for estimating SOC, comprising an operation of estimating the SOC of the battery cell by dividing the sum of the second reference capacity corresponding to the second OCV range and the charge capacity by the sum of the first reference capacity and the second reference capacity.

15. In paragraph 13, The operation of estimating the SOC of the above battery cell is as follows: When the second estimation algorithm is identified among the plurality of estimation algorithms, an operation of estimating the second SOC by performing an extended Kalman filter operation based on the second SOC-OCV relationship information and the OCV value of the battery cell; An operation of calculating a first DoD (Depth of Discharge) corresponding to the second OCV range based on the second SOC; An operation of calculating a discharge capacity based on the specified OCV value by multiplying the first DoD and the second reference capacity corresponding to the second OCV range; An operation of calculating a second DoD of the battery cell corresponding to the entire OCV range of the battery cell by dividing the sum of the first reference capacity and the discharge capacity corresponding to the first OCV range by the sum of the first reference capacity and the second reference capacity, and A method for estimating SOC, comprising an operation of estimating SOC of the battery cell based on the second DoD.

16. In paragraph 1, The above processor is an electronic device that directly obtains the OCV data measured through a sensor or obtains the OCV data through communication from an external device.

17. An electronic device according to claim 5, wherein the specified OCV value is about 3.2 V.

18. In paragraph 10, A method for estimating SOC, wherein the operation of acquiring the above OCV data includes an operation of directly acquiring the OCV data measured through a sensor or acquiring the OCV data through communication from an external device.

19. A method for estimating SOC in accordance with claim 13, wherein the specified OCV value is about 3.2 V.

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