Electronic device and battery diagnosis method thereof

Abstract

An electronic device according to one embodiment disclosed herein comprises: a communication interface; memory in which at least one instruction is stored; and at least one processor for performing an operation by executing the at least one instruction, wherein the processor may acquire charging data corresponding to a predetermined SOC section of a battery, calculate a plurality of section OCV rates of change respectively corresponding to a plurality of unit SOC sections included in the predetermined SOC section on the basis of the charging data, and diagnose the battery on the basis of the plurality of section OCV rates of change.

Description

Diagnostic methods for electronic devices and their batteries

[0001] This application claims the benefit of priority based on Korean Patent Application No. 10-2024-0141428 dated October 16, 2024, and all contents disclosed in the document of said Korean Patent Application are incorporated herein as part of this specification.

[0002] The embodiments disclosed in this document relate to an electronic device and a method for diagnosing its battery.

[0003] Recently, active research and development on secondary batteries has been underway. Here, the term "secondary battery" refers to a rechargeable battery, 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.

[0004] As the applications of such secondary batteries expand, the importance of technology regarding management systems for more efficient use and management is increasing. In particular, management systems must be able to accurately diagnose the performance and types of degradation of secondary batteries to appropriately adjust charging or discharging output and capacity utilization strategies.

[0005] Generally, State of Health (SOH) is used as a performance evaluation metric for secondary batteries. Since calculating the SOH of a secondary battery requires accurate values ​​for State of Charge (SOC) and capacity at Begin of Life (BOL), the battery's specifications must be considered. However, battery specifications are defined values ​​under fixed conditions, and variations may occur due to the production process and field usage. Therefore, there is a need for an indicator to accurately diagnose the battery's condition.

[0006] According to one embodiment of the present disclosure, an electronic device and a battery performance diagnosis method thereof can be provided, which can calculate an OCV strain rate for each unit section from battery charging data and diagnose the battery based on the OCV strain rate of the unit section.

[0007] 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.

[0008] An electronic device according to one embodiment of the present disclosure includes a communication interface, a memory storing at least one instruction, and at least one processor that performs an operation by executing the at least one instruction. The at least one processor acquires charging data corresponding to a predetermined SOC range of a battery, calculates a plurality of range OCV strain rates corresponding to each of a plurality of unit SOC ranges included in the predetermined SOC range based on the charging data, and can diagnose the battery based on the plurality of range OCV strain rates.

[0009] In an electronic device according to one embodiment of the present disclosure, the at least one processor can calculate the OCV strain corresponding to the unit SOC section based on the required charging current amount of the unit SOC section and the reference required charging current amount at the BOL (begin of life) of the battery.

[0010] In an electronic device according to one embodiment of the present disclosure, the reference required charging current amount may have the same value for each of the plurality of unit SOC intervals.

[0011] In an electronic device according to one embodiment of the present disclosure, the at least one processor can calculate the required charging current amount for the unit SOC section by integrating the real-time current value of the battery for a time section corresponding to the unit SOC section.

[0012] In an electronic device according to one embodiment of the present disclosure, the at least one processor calculates a first cumulative OCV strain and a second cumulative OCV strain based on two or more of the segment OCV strains corresponding to each of a first segment which is at least part of the predetermined SOC segment and a second segment different from the first segment, and can diagnose the performance of the battery based on the first cumulative OCV strain and the second cumulative OCV strain.

[0013] In an electronic device according to one embodiment of the present disclosure, the at least one processor can determine a decay section in which the required charging current of the battery is reduced based on the charging data.

[0014] In an electronic device according to one embodiment of the present disclosure, the at least one processor determines a first point and a second point at a predetermined SOC interval based on a decay start point where the decay section begins, wherein the first section is a section from the first point to a decay end point where the decay section ends, and the second section may be a section from the second point to the decay end point.

[0015] In an electronic device according to one embodiment of the present disclosure, the at least one processor can calculate the first accumulated OCV strain and the second accumulated OCV strain by accumulating the section OCV strain corresponding to each of the first section and the second section.

[0016] In an electronic device according to one embodiment of the present disclosure, the difference between the performance of the battery and the performance of the battery in BOL may be the difference between the first cumulative OCV strain rate reflecting the second cumulative OCV strain rate and the weighting factor.

[0017] In an electronic device according to one embodiment of the present disclosure, the weight may be a constant between 0 and 1 determined based on the characteristics of the battery.

[0018] In an electronic device according to one embodiment of the present disclosure, the at least one processor estimates the degree of degradation of the battery according to the degradation type based on a differential capacity which is the amount of change in the required charging current amount with respect to the instantaneous voltage value of the battery in the decay section, and the degradation type of the battery may include positive degradation, negative degradation, and LLI (loss of lithium inventory) degradation.

[0019] In an electronic device according to one embodiment of the present disclosure, the at least one processor can estimate that among the degradation types of the battery, the positive degradation has progressed the most when the SOC of the first minimum point of the differential capacity in the BOL state of the battery in the decay section is smaller than the SOC of the second minimum point of the differential capacity of the battery, and the differential capacity at the first minimum point is larger than the differential capacity at the second minimum point.

[0020] In an electronic device according to one embodiment of the present disclosure, the at least one processor can estimate that among the degradation types of the battery, the LLI degradation has progressed the most when the SOC of the first minimum point of the differential capacity in the BOL state of the battery in the decay section is smaller than the SOC of the second minimum point of the differential capacity in the BOL state of the battery, and the differential capacity at the first minimum point is smaller than the differential capacity at the second minimum point.

[0021] In an electronic device according to one embodiment of the present disclosure, the at least one processor may estimate that among the degradation types of the battery, the negative degradation has progressed the most when the SOC of the first minimum point of the differential capacity in the BOL state of the battery in the decay section is greater than the SOC of the second minimum point of the differential capacity in the BOL state of the battery.

[0022] A method for diagnosing a battery performed by an electronic device according to one embodiment of the present disclosure may include the steps of: acquiring charging data corresponding to a predetermined SOC range of the battery; calculating a plurality of range OCV strain rates corresponding to each of a plurality of unit SOC ranges included in the predetermined SOC range based on the charging data; and diagnosing the battery based on the plurality of range OCV strain rates.

[0023] A recording medium according to one embodiment of the present disclosure may be a computer-readable recording medium that records a program to be executed in an electronic device performing a method for diagnosing a battery according to one embodiment described above.

[0024] According to the embodiments disclosed in this document, the OCV strain rate for each SOC range can be calculated using data obtained during battery charging, and the performance of the battery can be accurately diagnosed.

[0025] According to the embodiments disclosed in this document, the degree of degradation of the battery by degradation type can be estimated using the OCV strain calculated for each section.

[0026] The effects of the invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by a person skilled in the art from the description in the claims.

[0027] FIG. 1 is a block diagram of an electronic device according to one embodiment of the present disclosure.

[0028] FIG. 2 is an example of charging data according to one embodiment of the present disclosure.

[0029] FIG. 3 is a drawing for explaining an example of a method for calculating the OCV strain rate in sections according to one embodiment of the present disclosure.

[0030] FIG. 4 is a drawing illustrating an example of a damping section according to one embodiment of the present disclosure.

[0031] FIG. 5 is a drawing for explaining an example of diagnosing the performance of a battery according to one embodiment of the present disclosure.

[0032] FIG. 6 is an exemplary diagram illustrating the performance of a battery calculated according to one embodiment of the present disclosure.

[0033] FIG. 7 is a graph illustrating an example of estimating the degree of degeneration by degeneration type according to an embodiment of the present disclosure.

[0034] FIG. 8 is a graph illustrating an example of estimating the degree of degeneration by degeneration type according to an embodiment of the present disclosure.

[0035] FIGS. 9a to 9c are graphs illustrating an example of estimating the degree of degeneration by degeneration type according to an embodiment of the present disclosure.

[0036] FIG. 10 is a flowchart of a method for an electronic device to diagnose a battery according to one embodiment of the present disclosure.

[0037] In describing the embodiments, technical details that are well known in the technical field to which this disclosure belongs and are not directly related to this disclosure are omitted. This is intended to convey the essence of this disclosure more clearly without obscuring it by omitting unnecessary explanations.

[0038] For the same reason, some components in the attached drawings have been exaggerated, omitted, or schematically depicted. Additionally, the size of each component does not entirely reflect its actual dimensions. Identical or corresponding components in each drawing have been assigned the same reference numbers.

[0039] The advantages and features of the present disclosure and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below but may be implemented in various different forms. The embodiments provided are merely to ensure that the 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. Throughout the specification, the same reference numerals refer to the same components.

[0040] At this time, it will be understood that each block of the process flow diagrams and combinations of the flow diagrams can be executed by computer program instructions. Since these computer program instructions can be loaded into the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing equipment, the instructions executed through the processor of the computer or other programmable data processing equipment create means for performing the functions described in the flow diagram block(s). Since these computer program instructions can also be stored in computer-available or computer-readable memory that can be directed toward the computer or other programmable data processing equipment to implement functions in a specific way, the instructions stored in such computer-available or computer-readable memory can also produce a manufactured item containing means of instruction for performing the functions described in the flow diagram block(s). Since computer program instructions can also be loaded onto a computer or other programmable data processing equipment, the instructions that execute the computer or other programmable data processing equipment by creating a process that is executed by a computer through a series of operation steps performed on the computer or other programmable data processing equipment can also provide steps for executing the functions described in the flow diagram block(s).

[0041] Additionally, each block may represent a module, segment, or part of code containing one or more executable instructions for executing a specific logical function(s). It should also be noted that in some alternative execution examples, the functions mentioned in the blocks may occur out of order. For instance, two blocks described in succession may actually be executed substantially simultaneously, or the blocks may be executed in reverse order according to their corresponding functions.

[0042] In this embodiment, the term "part" refers to a software or hardware component, such as an FPGA or ASIC, and the "part" performs certain roles. However, the meaning of "part" is not limited to software or hardware. The "part" may be configured to reside in an addressable storage medium or configured to operate one or more processors. Thus, for example, the "part" includes components such as software components, object-oriented software components, class components, and task components, as well as processes, functions, attributes, 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 "parts" may be combined into a smaller number of components and "parts" or further separated into additional components and "parts." Furthermore, the components and "parts" may be implemented to operate one or more CPUs within a device or secure multimedia card.

[0043] The expression “at least one of a, b, and c” described throughout the specification may include ‘a alone’, ‘b alone’, ‘c alone’, ‘a and b’, ‘a and c’, ‘b and c’, or ‘a, b, and c all’.

[0044] The "terminal" mentioned below may be implemented as a computer or portable terminal capable of connecting to a server or other terminal via a network. Here, the computer includes, for example, a notebook, desktop, or laptop equipped with a web browser, and the portable terminal is a wireless communication device that ensures portability and mobility, and may include all types of handheld-based wireless communication devices such as IMT (International Mobile Telecommunication), CDMA (Code Division Multiple Access), W-CDMA (W-Code Division Multiple Access), LTE (Long Term Evolution), communication-based terminals, smartphones, tablet PCs, etc.

[0045] Embodiments of the present disclosure are described below with reference to the attached drawings so that those skilled in the art can easily implement them. However, the present disclosure may be embodied in various different forms and is not limited to the embodiments described herein.

[0046] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the attached drawings.

[0047] FIG. 1 is a block diagram of an electronic device (100) according to one embodiment of the present disclosure.

[0048] Referring to FIG. 1, the electronic device (100) may include a communication interface (110), a memory (120), and a processor (130). According to an embodiment, the electronic device (100) illustrated in FIG. 1 may further include at least one component (e.g., a display, an input device, or an output device) in addition to the components illustrated in FIG. 1.

[0049] According to one embodiment, the electronic device (100) may be implemented as at least one of a notebook, desktop, laptop, and server computing device that receives and processes battery data from an external electronic device (e.g., a vehicle).

[0050] According to one embodiment, the communication interface (110) establishes a wired communication channel and / or a wireless communication channel between the electronic device (100) and an external electronic device, and can transmit and receive data with the external electronic device through the established communication channel. According to one embodiment, the communication interface (110) can receive charging data corresponding to a predetermined SOC range of the battery from the external electronic device and / or an external server.

[0051] Here, communication, that is, the transmission and reception of data, can be performed via wired or wireless means. To this end, the communication interface (110) 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 to transmit and receive data, a short-range communication module that uses a communication method of the WLAN (Wireless Local Area Network) family such as Wi-Fi, a communication method of the WPAN (Wireless Personal Area Network) family such as Bluetooth or Zigbee, a satellite communication module that uses a GNSS (Global Navigation Satellite System) such as GPS (Global Positioning System), or a combination thereof.

[0052] According to one embodiment, the memory (120) may include volatile memory and / or non-volatile memory.

[0053] According to one embodiment, the memory (120) may store data used by at least one component of the electronic device (100) (e.g., processor (130)). For example, the data may include software (or related instructions), input data, or output data. For example, the input data may be battery charging data and the output data may be battery diagnostic results. In one embodiment, the instruction may cause the electronic device (100) to perform operations defined by the instruction when executed by the processor (130).

[0054] According to one embodiment, the processor (130) may be implemented as a computer or a similar device according to hardware, software, or a combination thereof. Hardware-wise, the processor (130) may be implemented in the form of an electronic circuit that processes electrical signals to perform control functions, and software-wise, it may be implemented in the form of a program that drives the hardware processor (130). According to one embodiment, the processor (130) may be operatively connected to a component included in the electronic device (100) (e.g., a communication interface (110) and / or a memory (120)) to control the connected component.

[0055] According to one embodiment, the processor (130) may include a central processing unit, an application processor, a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor.

[0056] Meanwhile, unless otherwise specifically mentioned in the following description, the operation of the electronic device (100) may be interpreted as being performed under the control of the processor (130).

[0057] Hereinafter, a method for an electronic device (100) to diagnose a battery is described with reference to FIGS. 2, FIGS. 3, FIGS. 4, FIGS. 5, FIGS. 6, FIGS. 7, FIGS. 8 and FIGS. 9a to 9c.

[0058] According to one embodiment, the electronic device (100) can acquire charging data of the battery. At this time, the electronic device (100) may be a battery management device (or battery management system) (BMS) included in a battery pack, an on-board diagnostics (OBD) device included in an electric vehicle, a server or cloud device, and a charger and a charge / discharger.

[0059] According to one embodiment, the battery may be a vehicle battery placed in an electric vehicle or a hybrid electric vehicle (HEV), and the charging data may be log data regarding the amount of charge over time recorded while charging the battery, the amount of required charging current for the state value of the battery (e.g., state of charge (SOC), voltage, current, temperature, etc.), and events that occurred during charging (e.g., errors or omissions, etc.). As an example, the charging data may be data for a predetermined SOC range. That is, the charging data may be data for a partial SOC range where charging occurred (e.g., 40% to 100%) rather than the entire SOC range (0% to 100%), and in this case, the predetermined SOC range may be the SOC range where charging occurred.

[0060] FIG. 2 is an example of charging data according to one embodiment of the present disclosure.

[0061] According to one embodiment, the electronic device (100) can obtain a required charging current amount for a predetermined SOC range. Here, the required charging current amount may be a charging current amount required to increase by a unit SOC (e.g., 1%) from a specific SOC. As an example, the electronic device (100) can obtain battery charging data from any vehicle using a communication interface (110). The charging data may be a required charging current amount for the battery's SOC during battery charging.

[0062] Meanwhile, as the battery degrades with use, a section (hereinafter referred to as the 'decay section') (210) may appear in which the required charging current decreases in a specific SOC range. For example, referring to FIG. 2, the decrease in the required charging current in the decay section (210) becomes more severe as the driving distance increases, which contrasts with the fact that the required charging current of the battery in the BOL (begin of life) state is constant. In the decay section (210), the required charging current per unit SOC range of the battery decreases, and the SOC can increase with a small amount of current.

[0063] However, the SOC-OCV (open circuit voltage) table used to diagnose the condition of the battery is generated on the premise that the battery has the same degree of degradation across the entire SOC range. Therefore, deviations in the OCV strain rate by SOC may not be taken into account, such as the existence of a decay range (210) in the actual field. Therefore, a method is required to calculate the OCV strain rate for each SOC range and, accordingly, accurately diagnose the condition of the battery.

[0064] FIG. 3 is a drawing for explaining an example of a method for calculating the OCV strain rate in sections according to one embodiment of the present disclosure.

[0065] According to one embodiment, the electronic device (100) can calculate a plurality of segment OCV strain rates corresponding to each of a plurality of unit SOC segments included in a predetermined SOC segment based on charging data (300). At this time, each of the plurality of unit SOC segments may be a 1% segment. That is, when the predetermined SOC segment is 50% to 53%, the plurality of unit SOC segments may be a segment of 50% or more and less than 51%, a segment of 51% or more and less than 52%, and a segment of 52% or more and less than 53%.

[0066] The required charging current for a unit SOC range may be the required charging current for every 1% increase. For example, if a predetermined SOC range is 50% to 53%, the required charging current for a unit SOC range may be the required charging current when increasing from 50% to 51%, the required charging current when increasing from 51% to 52%, and the required charging current when increasing from 52% to 53%, respectively.

[0067] According to one embodiment, the electronic device (100) can calculate the required charging current amount for a unit SOC section by integrating the real-time current value of the battery for a time section corresponding to the unit SOC section. For example, the required charging current amount I for a unit SOC section corresponding to s(%) or more and less than s+1(%) req,s It can be equal to mathematical formula 1 below.

[0068] [Mathematical Formula 1]

[0069]

[0070] At this time, t s and t s+1 is the time when the SOC is s and s+1, and i is the real-time current value of the battery (A). Referring to Equation 1 above, for example, the required charging current I for a unit SOC interval corresponding to 50% or more and less than 51% req,50 silver, It may be a value corresponding to .

[0071] According to one embodiment, the electronic device (100) can calculate a plurality of OCV strain rates corresponding to each of a plurality of unit SOC intervals based on charging data.

[0072] As an example, the electronic device (100) can calculate the COV strain rate corresponding to the unit SOC range based on the required charging current amount of the unit SOC range and the reference required charging current amount (310) in the BOL of the battery. For example, the range OCV strain rate O corresponding to the unit SOC range corresponding to s(%) or more and less than s+1(%) s It can be equal to mathematical formula 2 below.

[0073] [Mathematical Formula 2]

[0074]

[0075] At this time, R BOL is the standard required charging current amount (310) of the unit SOC range in BOL. That is, the unit OCV strain may be the value obtained by dividing the required charging current amount of the corresponding unit SOC range by the standard required charging current amount (310). Here, the standard required charging current amount (310) refers to the required charging current amount in the BOL state of the battery, i.e., the initial state. Accordingly, according to one embodiment, the standard required charging current amount (310) may have the same value for each of the plurality of unit SOC ranges, as shown in the example in FIG. 3.

[0076] Referring to Mathematical Formula 2 above, for example, the required charging current O for the unit SOC range corresponding to 50% or more and less than 51% 50 silver, It may be a value corresponding to. Therefore, if the predetermined SOC range is an SOC range from 40% to 100%, the electronic device (100) can calculate 60 range OCV strain rates.

[0077] According to one embodiment, the electronic device (100) can diagnose a battery based on a plurality of interval OCV strain rates. For example, the electronic device (100) diagnosing the battery may include diagnosing the performance of the battery or estimating the degree of degradation of the battery. An embodiment in which the electronic device (100) estimates the degree of degradation of the battery will be described in detail later through FIGS. 7, FIGS. 8 and FIGS. 9a to 9c.

[0078] According to one embodiment, the electronic device (100) can calculate a first cumulative OCV strain and a second cumulative OCV strain based on two or more section OCV strains corresponding to each of a first section and a second section, which are at least a part of a predetermined SOC section.

[0079] At this time, the first section and the second section may be different SOC sections. For example, the electronic device (100) may determine the first section and the second section based on a decay section where the required charging current of the battery begins to decrease. Specifically, according to one embodiment, the electronic device (100) may determine a decay section where the required charging current of the battery decreases based on charging data.

[0080] For example, the decay section may be a section where the required charging current of the battery is below a preset threshold value compared to the reference required charging current. As another example, the decay section may be a section where the required charging current of the battery is below a preset threshold value compared to the reference required charging current for a preset section length or longer. As yet another example, the decay section may be a section where the required charging current of the battery increases above a preset upper threshold value compared to the reference required charging current and then decreases below a preset upper threshold value within a preset section length. This can be described as an embodiment that reflects the characteristics of the increase or decrease in the required charging current due to battery degradation. Meanwhile, the point where the decay section begins can be defined as the decay start point (320).

[0081] FIG. 4 is a drawing illustrating an example of a damping section according to one embodiment of the present disclosure.

[0082] FIG. 4 illustrates a graph of voltage values ​​for SOC of multiple batteries having different degrees of degradation. At this time, the voltage value of each of the multiple batteries may reflect the OCV strain of a predetermined SOC range. Referring to FIG. 4, it can be seen that the voltage (410) of the battery in BOL is 4.2 (V) when the SOC is 100 (%). However, it can be seen that the SOC is approximately 95 (%) when the voltage (411) of the first battery, which has undergone degradation, is 4.2 V, and the SOC is approximately 90 (%) when the voltage (412) of the second battery, which has undergone more degradation than the first battery, is 4.2 V. This is a phenomenon that occurs as the OCV strain increases due to the degradation of the first and second batteries.

[0083] Below, we will describe the damping section (420) from the damping start point (421) to the damping end point (422) based on the second battery, and describe in detail an embodiment for calculating the accumulated OCV strain rate.

[0084] According to one embodiment, the electronic device (100) can determine a first point and a second point before and after a predetermined SOC interval based on a damping start point (421) where the damping interval begins. For example, the predetermined SOC interval is α (%), and the damping start point (421) is S Tstart , the damping end point (422) where the damping section ends is S Tend When saying that, the first point is (S Tstart -α), 2nd point (S Tstart It can be determined as +α). When the first point and the second point are determined as in the present embodiment, the required charging current at the first point may have a value greater than the required charging current at the second point due to the increase or decrease characteristic of the required charging current amount according to battery degradation.

[0085] According to one embodiment, the first section (430) is from the first point to the attenuation end point (422) S Tend The section up to, and the second section (440) is from the second point to the damping end point (422) S Tend It can be determined as a range up to.

[0086] According to one embodiment, the electronic device (100) can calculate a first accumulated OCV strain by accumulating two or more section OCV strains corresponding to a first section (430), and calculate a second accumulated OCV strain by accumulating two or more section OCV strains corresponding to a second section (440). The accumulated OCV strain is an indicator representing the OCV strain of a specific section, and can be calculated by summing all of the multiple section OCV strains corresponding to the specific section. For example, (S Tstart -α) from S Tend The first cumulative OCV strain BC OCV strain corresponding to the first section (430) up to can be as shown in Equation 3 below, (S Tstart +α) from S TendThe second cumulative OCV strain AC OCV strain corresponding to the second section (440) up to can be as shown in Equation 4 below.

[0087] [Mathematical Formula 3]

[0088]

[0089] [Mathematical Formula 4]

[0090]

[0091] According to one embodiment, the electronic device (100) can diagnose the battery based on a first cumulative OCV strain and a second cumulative OCV strain. As an example, the electronic device (100) can diagnose the performance of the battery based on the first cumulative OCV strain and the second cumulative OCV strain.

[0092] Meanwhile, calculating the battery's performance, i.e., SOH, using the decay interval is merely an example of diagnosing the battery based on the interval OCV strain, and using the interval OCV strain, the interval SOH can also be calculated for each SOC interval of the battery. In this case, the SOC interval corresponding to the interval SOH may be at least a part of a predetermined SOC interval included in the charging data.

[0093] Specifically, from S0 to S r The Segment SOH for the SOC interval up to can be as shown in Equation 5 below.

[0094] [Mathematical Formula 5]

[0095]

[0096] FIG. 5 is a drawing for explaining an example of diagnosing the performance of a battery according to one embodiment of the present disclosure.

[0097] According to one embodiment, the electronic device (100) can diagnose the performance (530) of the battery based on the difference between the first cumulative OCV strain rate (510) and the second cumulative OCV strain rate (520). At this time, the performance (530) of the battery can be evaluated using the state of health (SOH), which indicates the state of deterioration of the current battery relative to the battery's BOL, as an indicator. At this time, the performance (530) of the battery can decrease in proportion to the value obtained by subtracting the first cumulative OCV strain rate (510) from the second cumulative OCV strain rate (520).

[0098] Referring to FIG. 5, the first cumulative OCV strain rate (510) and the second cumulative OCV strain rate (520) for each battery case according to use are shown. Below, the battery corresponding to Case 5 of FIG. 5 will be used as an example for explanation.

[0099] According to one embodiment, the electronic device (100) can determine the battery performance (530) by subtracting the difference between the second cumulative OCV strain (520) and the first cumulative OCV strain (510) from the performance in BOL, which is 100%. That is, when the first cumulative OCV strain (510) is denoted as BC OCV strain and the second cumulative OCV strain (520) is denoted as AC OCV strain, the battery performance (530) SOH can be determined as shown in Equation 6 below.

[0100] [Mathematical Formula 6]

[0101]

[0102] Meanwhile, calculating the battery performance as in mathematical formula 6 may be semantically equivalent to subtracting the average or midpoint of the OCV strain of each of the first and second sections from the battery performance in BOL.

[0103] According to one embodiment, the electronic device (100) can determine the battery performance (530) by subtracting the difference between the second accumulated OCV strain (520) and the first accumulated OCV strain (510) with weights reflected from 100%, which is the performance in BOL. When the weight of the first accumulated OCV strain (510) is denoted as β, the battery performance (530) SOH may be equal to Equation 7 below.

[0104] [Mathematical Formula 7]

[0105]

[0106] As an example, the weight may be a constant between 0 and 1 determined based on the characteristics of the battery. Specifically, the weight may be a hyperparameter that is pre-set according to the characteristics of the battery, such as physical properties and composition.

[0107] FIG. 6 is an exemplary diagram illustrating the performance of a battery calculated according to one embodiment of the present disclosure.

[0108] FIG. 6 shows a graph representing the performance of a battery calculated by an electronic device (100) for batteries in the field using the section OCV strain rate according to the embodiments described above. The horizontal axis represents the distance traveled using the battery, and the vertical axis represents the calculated performance of the battery (SOH). As an example, the performance of the battery (SOH) may be a value calculated based on the aforementioned mathematical formula 7.

[0109] In addition, the brightness of each point represents the cumulative OCV strain (OCV strain(%)) of the entire SOC range of the corresponding battery, and as the brightness increases, it indicates that the battery has a larger OCV strain.

[0110] Referring to Fig. 6, it can be observed that the OCV strain tends to increase as the driving distance increases. Additionally, it can be observed that the battery performance tends to decrease as the driving distance increases. Additionally, it can be observed that the battery performance tends to decrease as the OCV strain increases.

[0111] FIG. 7 is a graph illustrating an example of estimating the degree of degeneration by degeneration type according to an embodiment of the present disclosure.

[0112] Referring to Fig. 7, a graph of the required charging current for each of the following is shown: a battery in the BOL state (Case 1), a battery with 2.5% positive degradation and 2.5% LLI degradation (Case 2), a battery with 4% positive degradation and 1% LLI degradation (Case 3), a battery with 1% positive degradation and 4% LLI degradation (Case 4), and a battery with 5% positive degradation and 5% LLI degradation (Case 5).

[0113] Positive and negative degradation refer to the phenomenon in which structural or chemical changes occur in the positive or negative electrode materials during the charging and discharging process, resulting in a decrease in battery capacity and a shortened lifespan. Low-Ion Lime Degradation refers to the phenomenon in which the electrolyte inside the battery degrades, causing a decrease in the total amount of usable ions within the electrolyte.

[0114] According to one embodiment, the electronic device (100) can estimate the degree of degradation of the battery by type of degradation based on the required charging current amount of a plurality of unit SOC sections. Referring to FIG. 7, the SOC section that appears strongly for each type of degradation can be identified. For example, when referring to the required charging current amount of a battery (Case 5) in which positive degradation has progressed by 5% and LLI degradation has progressed by 5%, i.e., the total degradation degree is 10%, it can be seen that the battery's performance is evaluated as 90% compared to the required charging current amount (710) of a battery in a BOL state (Case 1). Meanwhile, when referring to the required charging current amount of a battery (Case 3) in which positive degradation has progressed by 4% and LLI degradation has progressed by 1%, the electronic device (100) can identify the part where positive degradation and LLI degradation appear strongly by comparing the decay section (730) and the stable section (740) after the decay section (730).

[0115] Specifically, by referring to the decay section (730), it can be seen that the difference between a battery with a total degradation of 10% (Case 5) and a battery with a total degradation of 5% (positive degradation 4%, LLI degradation 1%) (Case 3) is approximately 5%. Therefore, according to one embodiment, the electronic device (100) can identify the total degradation of the battery based on the decay section (730).

[0116] As an example, the electronic device (100) can calculate the total degradation of the target battery (ratio of the minimum point of the required charging current of the Case 5 battery in the decay section (730) to the required charging current of the Case 1 battery (710)) by comparing it with a preset reference total degradation of the decay section (730) (e.g., the total degradation of the Case 1 battery). In the example of FIG. 7, when the electronic device (100) wants to know the total degradation of Case 5, it can determine that the total degradation of the Case 5 battery is twice the total degradation of the Case 3 battery by confirming that, in the decay section (730), the target ratio of the minimum point of the required charging current of the Case 5 battery relative to the Case 1 battery is twice the reference ratio of the minimum point of the required charging current of the Case 3 battery relative to the Case 1 battery. However, the battery serving as the standard for the total degradation level is not limited to Case 3 and may be changed to a battery having a different degradation level according to various embodiments.

[0117] Additionally, specifically, by referring to the stabilization section (740) after the decay section (730), it can be seen that the difference between a battery with a total degradation of 10% (anode degradation 5%, LLI degradation 5%) (Case 5) and a battery with a total degradation of 5% (anode degradation 4%, LLI degradation 1%) (Case 3) is about 1%. Therefore, according to one embodiment, the electronic device (100) can estimate the degradation of the battery by degradation type based on the stabilization section (740).

[0118] As an example, the electronic device (100) can calculate the positive degradation of the target battery (ratio of the minimum point of the required charging current of the Case 5 battery in the stable section (740) to the required charging current of the Case 1 battery (710)) by comparing it with a preset reference positive degradation of the target battery in the stable section (740) (e.g., the positive degradation of the Case 1 battery). In the example of FIG. 7, when the electronic device (100) wants to know the positive degradation of the Case 5 battery, it can determine that the positive degradation of the Case 5 battery is 1.25 times the positive degradation of the Case 3 battery by confirming that, in the stable section (740), the target ratio of the minimum point of the required charging current of the Case 5 battery relative to the Case 1 battery is 1.25 times the reference ratio of the minimum point of the required charging current of the Case 3 battery relative to the Case 1 battery. However, the battery serving as the standard for the standard positive degradation degree is not limited to Case 3 and may be changed to a battery having a different degradation degree according to various embodiments.

[0119] FIG. 8 is a graph illustrating an example of estimating the degree of degeneration by degeneration type according to an embodiment of the present disclosure.

[0120] Referring to FIG. 8, a graph (800) of the differential capacity (dq / dv) of a battery with respect to the SOC of the charging data is shown. The differential capacity graph (800) of the battery includes a differential capacity graph of a battery in a BOL state and a plurality of batteries having different degrees of degradation according to various degradation types.

[0121] According to one embodiment, the electronic device (100) can estimate the degree of degradation by type of degradation based on the required charging current amount of a plurality of unit SOC intervals. Specifically, the electronic device (100) can estimate at least one degree of degradation among positive degradation, negative degradation, and LLI degradation based on a minute change in the required charging current amount due to a minute voltage change included in the battery decay interval (810).

[0122] In one example, the electronic device (100) can estimate the degree of degradation by identifying the vicinity of the minimum point of the differential capacity of the BOL battery in the decay section (810) and the vicinity of the minimum point of the differential capacity of the target battery for which the degree of degradation by degradation type is to be estimated, and by estimating which type of degradation among positive degradation, negative degradation, and LLI degradation of the target battery has progressed strongly. The differential capacity is a value representing the change in the amount of electric charge during charging or discharging of the battery, and refers to the change in the amount of required charging current (Ah / V) relative to the instantaneous voltage value of the battery. Accordingly, the electronic device (100) can estimate the degree of degradation by degradation type based on the amount of change in the amount of required charging current relative to the instantaneous voltage value of a plurality of unit SOC sections included in the decay section (810) of the target battery (hereinafter referred to as 'differential capacity').

[0123] FIGS. 9a to 9c are graphs illustrating an example of estimating the degree of degeneration by degeneration type according to an embodiment of the present disclosure.

[0124] FIGS. 9a to 9c illustrate the differential capacity (910) of the battery in the BOL state during the decay period and the differential capacity (920) of the target battery.

[0125] According to one embodiment, the electronic device (100) may determine that, in a decay section, if the SOC at the minimum point of the differential capacity (920) of the target battery (hereinafter referred to as the "second minimum point") is greater than the SOC at the minimum point of the differential capacity (910) of the battery in the BOL state (hereinafter referred to as the "first minimum point"), either positive degradation or LLI degradation among the degradation types of the target battery has progressed the most. For example, the electronic device (100) may determine that, in a decay section, if the differential capacity (920) of the target battery and the differential capacity (910) of the battery in the BOL state have the shape shown in FIG. 9a and FIG. 9c, either positive degradation or LLI degradation among the degradation types of the target battery has progressed the most.

[0126] According to one embodiment, the electronic device (100) can determine that positive degradation has progressed the most among the degradation types of the target battery when the SOC at the second minimum point is greater than the SOC at the first minimum point and the value at the second minimum point is smaller than the value at the first minimum point. For example, the electronic device (100) can determine that positive degradation has progressed the most among the degradation types of the target battery when the differential capacity (920) of the target battery and the differential capacity (910) of the battery in the BOL state in the decay section have a shape as shown in FIG. 9a. As the voltage value rises rapidly compared to the required charging current amount of the target battery when moving from the first minimum point to the second minimum point, a decay phenomenon of the required charging current amount may occur by reducing the required charging current amount in the electronic device (100) after the second minimum point. At this time, even after the second minimum point, the difference between the differential capacity (920) of the target battery and the differential capacity (910) of the battery in the BOL state increases, and the decay phenomenon may intensify. Accordingly, the electronic device (100) can determine that positive degradation has progressed the most among the types of degradation of the target battery when the required charging current of the target battery decreases monotonically in the decay section.

[0127] According to one embodiment, the electronic device (100) can determine that among the degradation types of the target battery, LLI degradation has progressed the most when the SOC of the second minimum point is greater than the SOC of the first minimum point and the value at the second minimum point is greater than the value at the first minimum point. For example, the electronic device (100) can determine that among the degradation types of the target battery, LLI degradation has progressed the most when the differential capacity (920) of the target battery and the differential capacity (910) of the battery in the BOL state have a shape as shown in FIG. 9c during the decay section. Since the differential capacity (920) of the target battery has a larger value than the differential capacity (910) of the battery in the BOL state while approaching the first minimum point, the required charging current amount of the target battery can be controlled by the electronic device (100) in a direction of increasing. When moving from the first minimum point to the second minimum point, as the difference between the differential capacity (920) of the target battery and the differential capacity (910) of the battery in the BOL state decreases, the voltage rise is greater than the predicted value of the electronic device (100) compared to the previously increased required charging current of the target battery, and the required charging current of the target battery can be controlled in a direction that decreases. At this time, after the second minimum point, the difference between the differential capacity (920) of the target battery and the differential capacity (910) of the battery in the BOL state decreases, and the decay phenomenon can be mitigated. Accordingly, the electronic device (100) can determine that among the types of decay of the target battery, LLI decay has progressed the most if the decay amount of the required charging current of the target battery in the decay section becomes lower than a preset threshold value or increases compared to the decay amount in the decay section.

[0128] According to one embodiment, the electronic device (100) can determine that the negative degradation among the degradation types of the target battery has progressed the most when the SOC of the second minimum point is smaller than the SOC of the first minimum point. For example, the electronic device (100) can determine that the negative degradation among the degradation types of the target battery has progressed the most when the differential capacity (920) of the target battery and the differential capacity (910) of the battery in the BOL state have a shape as shown in FIG. 9b during the decay section. When moving from the first minimum point to the second minimum point, the differential capacity (920) of the target battery and the differential capacity (910) of the battery in the BOL state are rapidly reversed, and the increase in the voltage value relative to the required charging current of the target battery is rapidly reduced, so that it may become smaller than the predicted value of the electronic device (100). Even after the second minimum point, the differential capacity (920) of the target battery can continuously have a value greater than the differential capacity (910) of the battery in the BOL state, thereby mitigating the decay phenomenon. Accordingly, the electronic device (100) can determine that among the types of decay of the target battery, negative decay has progressed the most if the decay amount of the required charging current of the target battery in the decay section is lower or increases by more than a preset threshold value compared to the decay amount in the decay section.

[0129] Accordingly, the electronic device (100) can estimate that among the types of degradation of the target battery, LLI degradation or negative degradation has progressed the most when the degradation amount of the required charging current of the target battery in the degradation section is lower or increases by more than a preset threshold value compared to the degradation amount in the degradation section, but when the shape of the first minimum point and the second minimum point is as in FIG. 9b, it can be determined that negative degradation has progressed the most, and when it is as in FIG. 9c, it can be determined that LLI degradation has progressed the most.

[0130] FIG. 10 is a flowchart of a method for an electronic device to diagnose a battery according to one embodiment of the present disclosure. Since the method of FIG. 10 can be performed by the electronic device (100) of FIG. 1, descriptions that overlap with the foregoing content may be omitted and may be explained using the components of FIG. 1.

[0131] The embodiment illustrated in FIG. 10 is merely one example, and according to various embodiments of the present disclosure, the order of steps performed by the electronic device (100) may differ from that illustrated in FIG. 10, and some steps illustrated in FIG. 10 may be omitted, the order of steps may be changed, or steps may be merged.

[0132] Referring to FIG. 10, in step 1010, the electronic device can obtain charging data corresponding to a predetermined SOC range of the battery.

[0133] In step 1020, the electronic device can calculate a section OCV strain corresponding to each of a plurality of unit SOC sections included in a predetermined SOC section based on charging data.

[0134] According to one embodiment, the electronic device can calculate an OCV strain corresponding to a unit SOC range based on the required charging current amount of the unit SOC range and the reference required charging current amount in the BOL of the battery.

[0135] According to one embodiment, the reference required charging current amount may have the same value for each of the plurality of unit SOC intervals.

[0136] According to one embodiment, the electronic device can calculate the required charging current amount for a unit SOC section by integrating the real-time current value of the battery for a time section corresponding to a unit SOC section.

[0137] According to one embodiment, the electronic device can calculate a first cumulative OCV strain and a second cumulative OCV strain based on two or more section OCV strains corresponding to each of a first section which is at least part of a predetermined SOC section and a second section which is different from the first section.

[0138] In step 1030, the electronic device can diagnose the battery based on multiple interval OCV strain rates.

[0139] According to one embodiment, the electronic device can diagnose the performance of the battery based on a first cumulative OCV strain and a second cumulative OCV strain.

[0140] According to one embodiment, the electronic device can determine a decay section in which the required charging current of the battery is reduced based on charging data.

[0141] According to one embodiment, the electronic device may determine a first point and a second point at a predetermined SOC interval based on a decay start point where the decay section begins. In this case, the first section may be the section from the first point to the decay end point where the decay section ends, and the second section may be the section from the second point to the decay end point.

[0142] According to one embodiment, the electronic device can calculate a first accumulated OCV strain and a second accumulated OCV strain by accumulating the section OCV strain corresponding to each of the first section and the second section.

[0143] According to one embodiment, the difference between the performance of the battery and the performance of the battery in BOL may be the difference between the first cumulative OCV strain rate reflecting the second cumulative OCV strain rate and the weighting.

[0144] According to one embodiment, the weight may be a constant between 0 and 1 determined based on the characteristics of the battery.

[0145] According to one embodiment, the electronic device can estimate the degree of degradation of the battery by degradation type based on the differential capacity, which is the amount of change in the required charging current amount relative to the instantaneous voltage value of the battery in the decay section. At this time, the degradation types of the battery may include positive degradation, negative degradation, and LLI degradation.

[0146] According to one embodiment, if the SOC of the first minimum point of the differential capacity in the BOL state of the battery in the decay section of the electronic device is smaller than the SOC of the second minimum point of the differential capacity of the battery, and the differential capacity at the first minimum point is larger than the differential capacity at the second minimum point, it can be estimated that positive degradation has progressed the most among the types of battery degradation.

[0147] According to one embodiment, in the electronic device, if the SOC of the first minimum point of the differential capacity in the BOL state of the battery in the decay section is smaller than the SOC of the second minimum point of the differential capacity in the BOL state of the battery, and the differential capacity at the first minimum point is smaller than the differential capacity at the second minimum point, it can be estimated that among the types of battery degradation, LLI degradation has progressed the most.

[0148] According to one embodiment, if the SOC of the first minimum point of the differential capacity in the BOL state of the battery in the decay section of the electronic device is greater than the SOC of the second minimum point of the differential capacity in the BOL state of the battery, it can be estimated that among the types of battery degradation, negative degradation has progressed the most.

[0149] The electronic device according to the above-described embodiments may include a processor, memory for storing and executing program data, permanent storage such as a disk drive, a communication port for communicating with an external device, a touch panel, a key, an icon, etc., and a user interface device.

[0150] Methods implemented by the software or algorithms disclosed in this document may be implemented as a program and stored on a computer-readable recording medium (or storage medium). The program may include computer-readable code or program instructions for executing a plurality of steps. In one embodiment, the recording medium may be implemented as a device such as, for example, a server, a hard disk drive (HDD), a solid state drive (SSD), read-only memory (ROM), random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, or an optical data storage device. In one embodiment, if a camera of a machine such as a computer identifies a QR code or a document, the QR code or the document may also be considered a recording medium, and there is no limitation on the type of recording medium as long as it can be read and executed by a computer. In one embodiment, the program may be stored on a single recording medium, or it may be distributed and stored on multiple recording media within a networked computer system to execute parts of the program in a distributed manner.

[0151] In one embodiment, a computer-readable recording medium may be provided in the form of a non-transitory recording medium. Here, the term "non-transitory" means that the recording medium is a tangible device and is not a transient signal (e.g., electromagnetic waves), and is not intended to distinguish between cases where data stored on the recording medium is stored semi-permanently and cases where it is stored temporarily. Meanwhile, this is merely one embodiment, and the recording medium may be modified to be transitory.

[0152] The method according to one embodiment may be provided by being included in a computer program product. The computer program product may be distributed in the form of a computer-readable medium (e.g., CD-ROM), distributed online through an application store (e.g., upload, download), or distributed directly between two or more terminal devices. The method according to one embodiment may be implemented as the computer program itself.

[0153] 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 numbers of hardware and / or software configurations that execute specific functions. For example, the embodiments may employ integrated circuit configurations such as memory, processing, logic, look-up tables, etc., which can execute various functions by the control of one or more microprocessors or other control devices. Similar to how components may be implemented as software programming or software elements, the embodiments may be implemented in programming or scripting languages ​​such as C, C++, Java, assembler, etc., including various algorithms implemented as combinations of data structures, processes, routines, or other programming configurations. Functional aspects may be implemented as algorithms executed on one or more processors. Additionally, the embodiments may employ prior art for electronic configuration, signal processing, and / or data processing. Terms such as “mechanism,” “element,” “means,” and “configuration” may be used broadly and are not limited to mechanical and physical configurations. The above terms may include the meaning of a series of software processes (routines) in conjunction with processors, etc.

[0154] The aforementioned embodiments are merely examples, and other embodiments may be implemented within the scope of the claims set forth below.

Claims

1. In an electronic device, Communication interface; Memory in which at least one instruction is stored; and It includes at least one processor that performs an operation by executing the above at least one instruction, and The above-mentioned at least one processor is, Acquire charging data corresponding to a predetermined SOC range of the battery, and Based on the above charging data, a plurality of section OCV strain rates corresponding to each of the plurality of unit SOC sections included in the above predetermined SOC section are calculated, and An electronic device configured to diagnose the battery based on the above-mentioned plurality of interval OCV strain rates.

2. In Paragraph 1, The above-mentioned at least one processor is, An electronic device that calculates the OCV strain corresponding to the unit SOC section based on the required charging current amount of the unit SOC section and the reference required charging current amount at the BOL (begin of life) of the battery.

3. In Paragraph 2, The required charging current amount based on the above criteria is, An electronic device having the same value for each of the above plurality of unit SOC intervals.

4. In Paragraph 2, The above-mentioned at least one processor is, An electronic device that calculates the required charging current amount of the unit SOC section by integrating the real-time current value of the battery for a time interval corresponding to the unit SOC section.

5. In Paragraph 1, The above-mentioned at least one processor is, Based on two or more of the said section OCV strains corresponding to each of the first section, which is at least a part of the said predetermined SOC section, and the second section, which is different from the first section, a first cumulative OCV strain and a second cumulative OCV strain are calculated, and An electronic device that diagnoses the performance of the battery based on the first cumulative OCV strain and the second cumulative OCV strain.

6. In Paragraph 5, The above-mentioned at least one processor is, An electronic device that determines a decay section in which the required charging current of the battery decreases based on the above charging data.

7. In Paragraph 6, The above-mentioned at least one processor is, A first point and a second point at a predetermined SOC interval are determined based on the damping start point where the above damping section begins, and The above first section is a section from the above first point to the damping end point where the above damping section ends, and The electronic device, wherein the second section is the section from the second point to the attenuation end point.

8. In Paragraph 7, The above-mentioned at least one processor is, An electronic device that calculates the first accumulated OCV strain and the second accumulated OCV strain by accumulating the section OCV strain corresponding to each of the first section and the second section.

9. In Paragraph 5, The difference between the performance of the above battery and the performance of the above battery in BOL is, An electronic device that is the difference between the first cumulative OCV strain and the second cumulative OCV strain and the weighting factor.

10. In Paragraph 9, The above weights are, An electronic device, which is a constant between 0 and 1 determined based on the characteristics of the above battery.

11. In Paragraph 6, The above-mentioned at least one processor is, Based on the differential capacity, which is the amount of change in the required charging current amount with respect to the instantaneous voltage value of the battery in the above decay section, the degree of degradation of the battery by degradation type is estimated, and The above type of battery degradation is, An electronic device including anode degradation, cathode degradation, and LLI (loss of lithium inventory) degradation.

12. In Paragraph 11, The above-mentioned at least one processor is, An electronic device that estimates that the positive degradation of the battery has progressed the most among the degradation types, when the SOC of the first minimum point of the differential capacity in the BOL state of the battery in the above decay section is smaller than the SOC of the second minimum point of the differential capacity of the battery, and the differential capacity at the first minimum point is larger than the differential capacity at the second minimum point.

13. In Paragraph 11, The above-mentioned at least one processor is, An electronic device that estimates that among the degradation types of the battery, the LLI degradation is the most advanced when the SOC at the first minimum point of the differential capacity in the BOL state of the battery in the above decay section is smaller than the SOC at the second minimum point of the differential capacity in the BOL state of the battery, and the differential capacity at the first minimum point is smaller than the differential capacity at the second minimum point.

14. In Paragraph 11, The above-mentioned at least one processor is, An electronic device that estimates that among the degradation types of the battery, the negative degradation has progressed the most when the SOC of the first minimum point of the differential capacity in the BOL state of the battery in the above decay section is greater than the SOC of the second minimum point of the differential capacity in the BOL state of the battery.

15. A method for diagnosing a battery performed by an electronic device, A step of obtaining charging data corresponding to a predetermined SOC range of the battery; Based on the charging data above, a step of calculating a plurality of section OCV strain rates corresponding to each of a plurality of unit SOC sections included in the predetermined SOC section; and A method for diagnosing a battery, comprising the step of diagnosing the battery based on the plurality of interval OCV strain rates.

16. A computer-readable recording medium having a program for executing the method of paragraph 15 on an electronic device.

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