Method for determining battery condition and electronic device for performing the method

Abstract

A battery state determination method according to one embodiment may include: determining a first value of a model parameter of a battery model that estimates the state of a battery based on first sensing data measured from one or more sensors connected to a battery of an electronic device; determining a first state of charge (SOC) of a battery using the battery model and the first sensing data when the first value of the model parameter corresponds to a first threshold value; determining a second SOC when the second value of the model parameter corresponds to a second threshold value set for the model parameter; determining an integrated current value consumed in the battery during an interval between the first SOC and the second SOC; updating the value of a degradation parameter of the battery model based on the first SOC, the second SOC, and the integrated current value; and determining the state of the battery using the battery model in which the value of the degradation parameter has been updated.

Description

Technology Field

[0001] The following embodiments relate to a battery state estimation method and apparatus. Background Technology

[0002] For battery operation, the state of the battery can be estimated, and there are various methods for estimating this state. For example, the state of the battery can be estimated by integrating the battery's current or by using a battery model (e.g., an electrical circuit model).

[0003] As the frequency of battery exposure to operating environments where degradation is accelerated, such as high-speed charging, high-speed discharging, or low or high temperature environments, increases, the need to predict battery status information by reflecting the battery's degradation state may increase. means of solving the problem

[0005] A battery state determination method performed by an electronic device according to one embodiment may include: determining a first value of a model parameter of a battery model that estimates the state of the battery based on first sensing data measured from one or more sensors connected to the battery of the electronic device; determining a first state of charge (SOC) of the battery using the battery model and the first sensing data when the first value of the model parameter corresponds to a first threshold value; determining a second SOC when the second value of the model parameter corresponds to a second threshold value set for the model parameter; determining an integrated current value consumed in the battery during an interval between the first SOC and the second SOC; updating a value of a degradation parameter of the battery model based on the first SOC, the second SOC, and the integrated current value; and determining the state of the battery using the battery model in which the value of the degradation parameter has been updated.

[0006] The battery state determination method may further include the operation of determining a first model voltage of the battery using the battery model, the operation of determining a first model OCV of the battery using the battery model, and the operation of determining the first model overvoltage based on the first model voltage and the first model OCV.

[0007] The operation of determining the first SOC may include the operation of determining the first OCV (open circuit voltage) of the battery based on the first sensing voltage of the battery and the first model overvoltage among the first sensing data, and the operation of determining the first SOC corresponding to the first OCV.

[0008] The operation of determining the first SOC corresponding to the first OCV may include the operation of determining the first SOC corresponding to the first OCV using a look-up table (LUT) representing the relationship between the OCV and SOC of the battery.

[0009] The operation of determining the second SOC may include: acquiring second sensing data measured from one or more sensors connected to the battery; determining a second value of the model parameter based on the second sensing data; determining whether the second value of the model parameter corresponds to a second threshold value set for the model parameter; determining a second model overvoltage of the battery using the battery model when the second value of the model parameter corresponds to the second threshold value; determining a second OCV of the battery based on the second sensing voltage of the battery and the second model overvoltage among the second sensing data; and determining the second SOC corresponding to the second OCV.

[0010] The state of the above battery may include the State of Health (SOH) of the battery.

[0011] The above model parameter may be the cathode ion concentration.

[0012] The first threshold value set for the model parameter, which is the cathode ion concentration, may be a value between 0.85 and 0.65.

[0013] The second threshold value set for the model parameter, which is the cathode ion concentration, may be a value between 0.65 and 0.40.

[0014] The above degradation parameter may be the rate of change of the capacity of the positive active material.

[0015] The first threshold value set for the model parameter, which is the cathode ion concentration, may be a value between 0.40 and 0.20.

[0016] The second threshold value set for the model parameter, which is the cathode ion concentration, may be a value between 0.20 and 0.05.

[0017] The above degradation parameter may be an electrode balance shift.

[0018] The above electronic device may be a mobile terminal.

[0019] According to one embodiment, an electronic device comprises at least one processor including processing circuitry and a memory including one or more storage media for storing instructions, and when the instructions are executed individually or collectively by the at least one processor, the electronic device may: determine a first value of a model parameter of a battery model that estimates the state of the battery based on first sensing data measured from one or more sensors connected to the battery of the electronic device; if the first value of the model parameter corresponds to a first threshold value, determine a first state of charge (SOC) of the battery using the battery model and the first sensing data; if the second value of the model parameter corresponds to a second threshold value set for the model parameter, determine a second SOC; determine an integrated current value consumed in the battery during the interval between the first SOC and the second SOC; update a value of a degradation parameter of the battery model based on the first SOC, the second SOC and the integrated current value; and determine the state of the battery using the battery model with the updated value of the degradation parameter.

[0020] According to one embodiment, a mobile terminal comprises a display, a battery supplying power to the display, at least one processor including processing circuitry, and a memory including one or more storage media storing instructions, and when the instructions are executed individually or collectively by the at least one processor, the mobile terminal: acquires first sensing data measured from one or more sensors connected to the battery, determines a first value of a model parameter of a battery model that estimates the state of the battery based on the first sensing data, determines whether the first value of the model parameter corresponds to a first threshold value set for the model parameter, and if the first value of the model parameter corresponds to the first threshold value, determines a first model overvoltage of the battery using the battery model, determines a first OCV (open circuit voltage) of the battery based on the first sensing voltage of the battery and the first model overvoltage among the first sensing data, determines a first SOC (state of charge) corresponding to the first OCV, and a second value of the model parameter is to the model parameter A second OCV of the battery is determined based on the second model overvoltage of the battery determined in accordance with a second threshold value set for the battery, a second SOC corresponding to the second OCV is determined, a current integration value consumed in the battery during the interval between the first SOC and the second SOC is determined, the value of the degradation parameter of the battery model is updated based on the first SOC, the second SOC and the current integration value, and the state of the battery can be determined using the battery model in which the value of the degradation parameter is updated.

[0021] When the above instructions are executed individually or collectively by the at least one processor, the mobile terminal may be configured to: determine a first model voltage of the battery using the battery model, determine a first model OCV of the battery using the battery model, and determine a first model overvoltage based on the first model voltage and the first model OCV.

[0022] When the above commands are executed individually or collectively by the at least one processor, the mobile terminal may be configured to: acquire second sensing data measured from one or more sensors connected to the battery, determine a second value of the model parameter based on the second sensing data, determine whether the second value of the model parameter corresponds to a second threshold value set for the model parameter, and if the second value of the model parameter corresponds to the second threshold value, determine a second model overvoltage of the battery using the battery model, and determine a second OCV of the battery based on the second sensing voltage of the battery and the second model overvoltage among the second sensing data.

[0023] The above model parameter may be the cathode ion concentration.

[0024] The above degradation parameter may be the rate of change in the capacity of the positive active material or the electrode balance shift. Brief explanation of the drawing

[0026] FIG. 1 is a configuration diagram of a battery system according to one embodiment. FIG. 2 is a configuration diagram of an electronic device according to one embodiment. FIG. 3 is a diagram illustrating an electrochemical model according to one embodiment. Figure 4 illustrates the cell voltage, positive OCP, and negative OCP according to battery discharge, according to one example. FIG. 5 is a flowchart of a method for determining battery status according to one embodiment. Figure 6 is a flowchart of a method for determining model overvoltage according to one example. FIG. 7a illustrates a method for determining a first OCV for calculating the rate of change of capacity of a positive electrode active material according to one example. FIG. 7b illustrates a method for determining a second OCV to calculate the rate of change of capacity of a positive electrode active material according to one example. FIG. 8a illustrates a method for determining a first OCV for calculating an electrode balance shift according to one example. FIG. 8b illustrates a method for determining a second OCV for calculating an electrode balance shift according to one example. FIG. 9 is a flowchart of a method for determining the second OCV of a battery according to one example. FIG. 10a illustrates a fresh OCV curve that appears when the battery is in a fresh state, according to one example, and an adjusted OCV curve determined based on the SOCs determined during the use of the battery. FIG. 10b illustrates the initial battery capacity determined based on a fresh OCV curve and the current battery capacity determined based on an adjusted OCV curve, according to one example. FIG. 11 is a drawing for explaining a vehicle according to one example. FIG. 12 is a drawing for explaining a mobile terminal according to one example. FIG. 13 is a drawing for explaining an electronic device according to one example. FIG. 14 is a flowchart of a method for determining battery status according to one embodiment. Specific details for implementing the invention

[0027] Hereinafter, embodiments are described in detail with reference to the attached drawings. However, various modifications may be made to the embodiments, and thus the scope of the patent application is not limited or restricted by these embodiments. It should be understood that all modifications, equivalents, and substitutions to the embodiments are included within the scope of the rights.

[0028] The terms used in the embodiments are for illustrative purposes only and should not be interpreted as intended to be limiting. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, terms such as "comprising" or "having" are intended to indicate the existence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0029] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which the embodiments pertain. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this application.

[0030] In addition, when describing with reference to the attached drawings, identical components are assigned the same reference numeral regardless of drawing symbols, and redundant descriptions thereof are omitted. When describing embodiments, if it is determined that a detailed description of related prior art could unnecessarily obscure the essence of the embodiment, such detailed description is omitted.

[0031] In addition, terms such as first, second, A, B, (a), (b), etc., may be used when describing the components of the embodiments. These terms are intended only to distinguish the components from other components, and the nature, order, or sequence of the components is not limited by the terms. Where it is stated that a component is "connected," "combined," or "connected" to another component, it should be understood that the component may be directly connected or connected to the other component, but that another component may also be "connected," "combined," or "connected" between each component.

[0032] Components included in any one embodiment and components having common functions shall be described using the same names in other embodiments. Unless otherwise stated, the description in any one embodiment may also apply to other embodiments, and specific descriptions shall be omitted to the extent of overlap.

[0034] FIG. 1 is a configuration diagram of a battery system according to one embodiment.

[0035] Referring to FIG. 1, the battery system (100) includes a battery (110) and a battery state estimation device (120).

[0036] The battery (110) may be a rechargeable battery, such as one or more battery cells, battery modules, or battery packs.

[0037] The battery state estimation device (120) is a device that estimates (or determines) the battery state for the operation of the battery (110) and may include, for example, a Battery Management System (BMS). The battery state estimation device (120) senses the battery (110) using one or more sensors and collects sensing data. For example, the sensing data may include voltage data, current data, and / or temperature data. According to an embodiment, the battery state estimation device (120) may not include a sensor and may receive sensing data from an independent sensor or another device.

[0038] The battery state estimation device (120) can estimate state information of the battery (110) based on sensing data and output the result. The state information may include, for example, state of charge (SOC), relative state of charge (RSOC), state of health (SOH), and / or abnormality state information. The battery model used when estimating the state information is an electrochemical model, which is explained with reference to FIG. 3.

[0039] The battery state estimation device (120) can reflect the deterioration state of the battery (110) in the battery model and estimate state information reflecting the deterioration state of the battery (110).

[0040] The degradation factors of the battery (110) include not only an increase in simple resistance components but also various factors such as a decrease in the amount of active material of the positive or negative electrode and the occurrence of lithium plating (Li-plating). In particular, the pattern of degradation may vary depending on the usage pattern and usage environment of the battery user. For example, even if the reduction in capacity of the battery (110) due to degradation is the same, the internal state of the degraded battery (110) may differ. To more accurately reflect the degradation of the battery in the battery model, the degradation parameters of the battery estimated through the analysis of the response characteristics (e.g., voltage, etc.) of the degraded battery may be used to update the battery model.

[0041] A battery state estimation device (120) is described in detail below with reference to FIGS. 2 to 13.

[0043] FIG. 2 is a configuration diagram of an electronic device according to one embodiment.

[0044] The electronic device (200) includes a communication unit (210), a processor (220), and a memory (230). For example, the electronic device (200) may correspond to the battery state estimation device (120) described above with reference to FIG. 1.

[0045] According to one embodiment, the electronic device (200) may be included in a mobile terminal.

[0046] According to one embodiment, the electronic device (200) may be included in a vehicle.

[0047] The communication unit (210) is connected to the processor (220) and memory (230) to transmit and receive data. The communication unit (210) may be connected to other external devices to transmit and receive data. In the following, the expression "transmit and receive A" may indicate transmitting and receiving "information or data representing A".

[0048] The communication unit (210) may be implemented as a circuitry within the electronic device (200). For example, the communication unit (210) may include an internal bus and an external bus. As another example, the communication unit (210) may be an element connecting the electronic device (200) and an external device. The communication unit (210) may be an interface. The communication unit (210) may receive data from an external device and transmit the data to the processor (220) and memory (230).

[0049] The processor (220) processes data received by the communication unit (210) and data stored in memory (230). The "processor" may be a data processing device implemented in hardware having a circuit having a physical structure for executing desired operations. For example, the desired operations may include code or instructions included in a program. For example, the data processing device implemented in hardware may include a microprocessor, a central processing unit, a processor core, a multi-core processor, a multiprocessor, an Application-Specific Integrated Circuit (ASIC), or a Field Programmable Gate Array (FPGA).

[0050] The processor (220) executes computer-readable code (e.g., software) stored in memory (e.g., memory (230)) and instructions triggered by the processor (220).

[0051] The memory (230) stores data received by the communication unit (210) and data processed by the processor (220). For example, the memory (230) may store a program (or application, software). For example, the program to be stored may be a set of syntax that is coded to determine the state of the battery and can be executed by the processor (220).

[0052] According to one aspect, the memory (230) may include one or more volatile memory, non-volatile memory and RAM (Random Access Memory), flash memory, hard disk drive and optical disk drive.

[0053] The memory (230) stores a set of instructions (e.g., software) that operate the electronic device (200). The set of instructions that operate the electronic device (200) is executed by the processor (220).

[0054] The communication unit (210), processor (220), and memory (230) are described in detail below with reference to FIGS. 3 to 13.

[0056] FIG. 3 is a diagram illustrating an electrochemical model according to one embodiment.

[0057] Referring to Figure 3, the electrochemical model can estimate the remaining battery capacity by modeling internal physical phenomena of the battery, such as ion concentration and potential. In other words, the electrochemical model can be expressed as a physical conservation equation related to electrochemical reactions occurring at the electrode / electrolyte interface, the concentration of the electrode / electrolyte, and charge conservation. To this end, various model parameters such as shape (e.g., thickness, radius, etc.), open circuit potential (OCP), and physical properties (e.g., electrical conductivity, ionic conductivity, diffusion coefficient, etc.) are used.

[0058] In an electrochemical model, various state variables such as concentration and potential can be coupled with each other. The estimated voltage (310) of the battery estimated in the electrochemical model is the potential difference between the positive and negative ends, and the ion concentration distribution of the positive and negative electrodes affects the potential of the positive and negative electrodes (320). Additionally, the average ion concentration of the positive and negative electrodes can be estimated as the SOC (330) of the battery in the electrochemical model.

[0059] The ion concentration distribution may represent an ion concentration distribution (340) within the electrode or an ion concentration distribution (350) within active material particles located at specific positions within the electrode. The ion concentration distribution (340) within the electrode represents a surface ion concentration distribution or an average ion concentration distribution of active material particles located along the electrode direction, and the electrode direction may represent a direction connecting one end of the electrode (e.g., a boundary adjacent to a current collector) and the other end of the electrode (e.g., a boundary adjacent to a separator). Additionally, the ion concentration distribution (350) within the active material particles represents an ion concentration distribution inside the active material particles along the direction of the active material particles' centers, and the direction of the active material particles' centers may represent a direction connecting the center of the active material particles and the surface of the active material particles.

[0060] The measured voltage refers to the battery voltage measured through a voltage meter (or sensor), and the estimated voltage (310) may refer to the battery voltage estimated from a battery model.

[0061] The initial electrochemical model reflects the fresh state of a battery that has not undergone degradation, and as the battery degrades, the error between the estimated voltage (310) of the electrochemical model and the measured voltage of the actual battery that has degraded may gradually increase. Furthermore, even if updated degradation parameters are reflected in the electrochemical model, the battery continues to degrade depending on usage patterns or the environment, so the error between the estimated voltage (310) of the electrochemical model reflecting the previous degradation state and the measured voltage of the actual battery that has further degraded may gradually increase.

[0062] As the degradation of the battery progresses, the difference between the estimated voltage (310) and the measured voltage may gradually increase. Based on the difference in response characteristics between the estimated voltage (310) and the measured voltage, the battery state estimation device may estimate the amount of change in degradation parameters and reflect it in the electrochemical model. The degradation parameters are parameters representing the degradation state of the battery among a plurality of parameters included in the electrochemical model, and may include, for example, one or a combination of two or more of the SEI (solid electrolyte interphase) resistance of the negative electrode, the capacity of the positive active material, and the electrode balance shift.

[0063] In order to estimate the state of a battery (e.g., SOC or SOH) with higher accuracy by accurately updating the degradation parameters of the battery, the open circuit voltage (OCV) of the battery may need to be accurately determined. Below, with reference to FIGS. 4 to 10b, a method for determining multiple OCVs for multiple time points while the battery is discharging, and determining the state of the battery based on multiple SOCs determined based on the determined multiple OCVs, is described in detail.

[0065] Figure 4 illustrates the cell voltage, positive OCP, and negative OCP according to battery discharge, according to one example.

[0066] Cell voltage represents the measured voltage of the battery, V CA - V AN It can be determined as such, and as discharge due to battery use progresses, the size gradually decreases. Positive OCP decreases relatively steadily compared to negative OCP, and the slope of decrease gradually becomes smaller, whereas negative OCP has a relatively small slope initially compared to positive OCP, and may have a steep slope at the end.

[0067] According to one embodiment, the negative electrode OCP may initially have a slope of 0 or a slope close to 0. The reduction in the capacity of the positive electrode active material may be determined in the section (410) where the slope of the negative electrode OCP is 0 or a slope close to 0. The section (410) may correspond to a section where the battery's SOC is high. In other words, the section (410) where the reduction in the capacity of the positive electrode active material is estimated may be a section where the battery's state information (e.g., SOC) is greater than a predetermined threshold or falls within a predetermined range. Additionally, by utilizing the fact that the battery's state information has a certain correlation with the battery's ion concentration and active material capacity, the section (410) may be detected based on either the battery's negative electrode ion concentration or the active material capacity in addition to the battery's state information.

[0068] The capacity of the cathode active material is a quantitative representation of the phenomenon in which the active material capable of accepting lithium ions in the cathode decreases as it degrades; the more severe the degradation, the greater the reduction in the cathode active material's capacity.

[0069] According to one embodiment, the positive OCP may have a slope of 0 or a slope close to 0 in the later stages. The electrode balance shift may be determined in the interval (420) where the slope of the positive OCP is 0 or a slope close to 0. The interval (420) may correspond to a interval where the battery's SOC is small. In other words, the interval (420) where the electrode balance shift is estimated may be a interval where the battery's state information (e.g., SOC) is greater than a predetermined threshold or falls within a predetermined range. Additionally, by utilizing the fact that the battery's state information has a constant correlation with the battery's ion concentration and electrode balance shift, the interval (420) may be detected based on either the negative ion concentration or the positive ion concentration in addition to the battery's state information.

[0070] The value of the degradation parameter can be updated in at least one of the sections (410) and (420), and the degradation parameter can be used to update the battery model.

[0072] FIG. 5 is a flowchart of a method for determining battery status according to one embodiment.

[0073] The operations 505 to 555 of FIG. 5 may be performed by an electronic device (e.g., the battery state estimation device (120) of FIG. 1 or the electronic device (200) of FIG. 2). For example, the electronic device may include at least one processor (e.g., the processor (220) of FIG. 2) and a memory (e.g., the memory (230) of FIG. 2).

[0074] In operation 505, the electronic device may acquire first sensing data measured from one or more sensors connected to the battery. For example, the first sensing data may include voltage data, current data and / or temperature data.

[0075] In operation 510, the electronic device may determine a first value of a model parameter of a battery model that estimates the state of the battery based on first sensing data. For example, the battery model may be an electrochemical model. For example, the model parameter may include a negative electrode ion concentration, a positive electrode ion concentration, a negative electrode OCP, a positive electrode OCP, electrical conductivity, ionic conductivity, diffusion coefficient, SEI resistance of the negative electrode, capacity of the positive electrode active material, and / or electrode balance shift. The SEI resistance of the negative electrode, the capacity of the positive electrode active material, and the electrode balance shift may be model parameters and degradation parameters.

[0076] In operation 515, the electronic device can determine whether a first value of a model parameter corresponds to a first threshold value set for the model parameter. For example, the model parameter may be a cathode ion concentration.

[0077] The first threshold value may correspond to the start time of the aforementioned interval (410) with reference to FIG. 4. The interval (410) may be a interval set to calculate the rate of change of the capacity of the positive active material as a value of the degradation parameter. For example, if the model parameter is the negative ion concentration, the first threshold value set for the model parameter may be a value between 0.85 and 0.65.

[0078] The first threshold value may correspond to the start time of the section (420) described above with reference to FIG. 4. The section (420) may be a section set to calculate the electrode balance shift as a value of the degradation parameter. For example, if the model parameter is the cathode ion concentration, the first threshold value set for the model parameter may be a value between 0.40 and 0.20.

[0079] If the first value of the model parameter does not correspond to the first threshold value set for the model parameter, operations 505 to 515 may be performed repeatedly.

[0080] In operation 520, the electronic device may determine a first model overvoltage (or overpotential) of the battery using the battery model when the first value of the model parameter corresponds to a first threshold value set for the model parameter. For example, the model overvoltage may be a value calculated using the battery model. For example, the model overvoltage may be calculated based on the activation overpotential, the ohmic overpotential, and the concentration overpotential.

[0081] According to one embodiment, the model overvoltage may be the difference between the model OCV calculated using the battery model and the model voltage, which is the voltage of the battery calculated using the battery model. Below, a method for determining the first model overvoltage is described in detail with reference to FIG. 6.

[0082] In operation 525, the electronic device can determine a first OCV of the battery based on a first sensing voltage of the battery and a first model overvoltage among the first sensing data. For example, the sum of the first sensing voltage of the battery and the first model overvoltage can be determined as the first OCV.

[0083] In operation 530, the electronic device can determine a first SOC corresponding to a first OCV. According to one embodiment, the first SOC corresponding to the first OCV can be determined based on a look-up table (LUT) that is predefined for the relationship between the OCV and SOC of the battery. For example, if the state of the battery changes, the LUT can be redefined to correspond to the state of the battery. For example, as the values ​​of one or more model parameters are updated, the OCV curve for SOH or available battery capacity may change, and the LUT for SOC can be redefined to correspond to the changed OCV curve.

[0084] In operation 535, the electronic device may determine a second OCV based on a second model overvoltage of the battery determined as the second value of the model parameter corresponds to a second threshold value set for the model parameter. For example, the model parameter may be a negative ion concentration.

[0085] The second threshold value may correspond to the end point of the section (410) described above with reference to FIG. 4. For example, if the model parameter is the negative ion concentration and the degradation parameter is the rate of change of the capacity of the positive active material, the second threshold value set for the model parameter may be a value between 0.65 and 0.40.

[0086] The second threshold value may correspond to the end point of the section (420) described above with reference to FIG. 4. For example, if the model parameter is cathode ion concentration and the degradation parameter is electrode balance shift, the second threshold value set for the model parameter may be a value between 0.20 and 0.05.

[0087] The electronic device can determine the second model overvoltage (or overpotential) of the battery using the battery model when the second value of the model parameter corresponds to a second threshold value set for the model parameter.

[0088] The electronic device can determine the second OCV of the battery based on the second sensing voltage and the second model overvoltage of the battery among the second sensing data. The second sensing data may refer to sensing data measured at a different time from the first sensing data among the sensing data that is measured continuously or repeatedly. A method for determining the second OCV is described in detail below with reference to FIG. 9.

[0089] In operation 540, the electronic device can determine a second SOC corresponding to the second OCV. According to one embodiment, the second SOC corresponding to the second OCV can be determined based on a predefined LUT regarding the relationship between the OCV and SOC of the battery. The LUT used to determine the second SOC may be the same as the LUT used to determine the first SOC.

[0090] In operation 545, the electronic device can determine the current integration value consumed from the battery during the interval between the first SOC and the second SOC. For example, the current integration value may be the accumulated charge amount for the interval between the first time point when the first SOC is calculated (or, the time point when the first sensing data is acquired) and the second time point when the second SOC is calculated (or, the time point when the second sensing data is acquired).

[0091] In operation 550, the electronic device can update the value of the degradation parameter of the battery model based on the first SOC, the second SOC, and the current integration value.

[0092] According to one embodiment, the degradation parameter may be the rate of change of the capacity of the positive active material. The rate of change of the capacity of the positive active material may be determined for the interval (410) described above with reference to FIG. 4. For example, an electronic device may calculate the current battery capacity available at a current point in time (e.g., a second point in time). The electronic device may calculate the rate of change of capacity based on the current battery capacity and the initial battery capacity. Based on the calculated rate of change of battery capacity, the rate of change of the capacity of the positive active material may be determined. For example, the rate of change of battery capacity may be considered as the rate of change of the capacity of the positive active material.

[0093] The current battery capacity can be calculated by [Equation 1].

[0094] [Mathematical Formula 1]

[0095]

[0096] In [Mathematical Equation 1], Q now is the current battery capacity, and d Q is the current integration value, SOC1 is the first SOC, and SOC2 is the second SOC.

[0097] The rate of change in battery capacity can be calculated by [Equation 2].

[0098] [Mathematical Formula 2]

[0099]

[0100] In [Mathematical Equation 2], Q ratio is the rate of change in battery capacity, and Q now is the current battery capacity, and Q init This may be the initial battery capacity. The initial battery capacity may be the battery capacity that appears when the battery is fresh.

[0101] Q, the rate of change in battery capacity ratio anode capacity change rate CA ratio It can be determined as.

[0102] According to one embodiment, the degradation parameter may be an electrode balance shift. The electrode balance shift may be determined for the section (420) described above with reference to FIG. 4. The electrode balance shift may be determined based on the battery capacity change rate calculated through [Equation 1] and [Equation 2]. For example, the electrode balance shift may be determined using the following [Equation 3].

[0103] [Mathematical Formula 3]

[0104]

[0105] In [Equation 3], EBshift is the electrode balance shift, and Q ratio This can be the rate of change in anode capacity.

[0106] The electronic device can update the value of the degradation parameter by updating at least one of the rate of change of capacity of the positive active material to be applied to the battery model and the calculated electrode balance shift.

[0107] In operation 555, the electronic device can determine the state of the battery using a battery model in which the values ​​of the degradation parameters have been updated. For example, the electronic device can adjust the OCV curve for the available battery capacity. The electronic device can generate a standard discharge overvoltage curve based on the adjusted OCV curve. The electronic device can reconsider the current battery capacity of the battery based on the standard discharge overvoltage curve. The electronic device can calculate the SOH as the state of the battery using [Equation 4].

[0108] [Mathematical Formula 4]

[0109]

[0110] In [Mathematical Equation 4], Q new is the recrystallized current battery capacity, and Q init This could be the initial battery capacity.

[0112] Figure 6 is a flowchart of a method for determining model overvoltage according to one example.

[0113] According to one embodiment, operations 610 to 630 of FIG. 6 may be associated with operation 520 described above with reference to FIG. 5. For example, operation 520 may include operations 610 to 630.

[0114] Operations 610 to 630 may be performed by an electronic device (e.g., the battery state estimation device (120) of FIG. 1 or the electronic device (200) of FIG. 2). For example, the electronic device may include at least one processor (e.g., the processor (220) of FIG. 2) and a memory (e.g., the memory (230) of FIG. 2).

[0115] In operation 610, the electronic device can determine a first model voltage of the battery using a battery model. The first model voltage may be the voltage of the battery estimated using the battery model.

[0116] In operation 620, the electronic device can determine the first model OCV of the battery using the battery model. The first model OCV may be the OCV of the battery estimated using the battery model.

[0117] In operation 630, the electronic device can determine the first model overvoltage based on the first model voltage and the first model OCV. For example, the value obtained by subtracting the first model voltage from the first model OCV can be determined as the first model overvoltage.

[0119] FIG. 7a illustrates a method for determining a first OCV for calculating the rate of change of capacity of a positive electrode active material according to one example.

[0120] The x-axis of the illustrated graph can correspond to the time during which the battery discharge proceeds or the amount of decrease in SOC.

[0121] According to one embodiment, at time a, a first value of a model parameter may correspond to a first threshold value set for the model parameter. For example, a value of the cathode ion concentration determined based on sensing data may correspond to a first threshold value (e.g., 0.75) at time a. Time a may be included in the interval (410) described above with reference to FIG. 4. A first model voltage (714) of the battery may be calculated using the battery model. A first model OCV (716) of the battery may be calculated using the battery model. The model overvoltage may be determined as the value obtained by subtracting the first model voltage (714) from the first model OCV (716). The first OCV (718) may be determined as the sum of the model overvoltage and the first sensing voltage (712).

[0122] According to one embodiment, a first SOC corresponding to a first OCV (718) can be determined. For example, a first SOC corresponding to a first OCV can be determined based on a predefined LUT for the relationship between the battery's OCV curve (703) and SOC.

[0124] FIG. 7b illustrates a method for determining a second OCV to calculate the rate of change of capacity of a positive electrode active material according to one example.

[0125] The x-axis of the illustrated graph can correspond to the time during which the battery discharge proceeds or the amount of decrease in SOC.

[0126] According to one embodiment, at time b, a second value of the model parameter may correspond to a second threshold value set for the model parameter. For example, the value of the cathode ion concentration determined based on the sensing data may correspond to the second threshold value (e.g., 0.5) at time b. Time b may be included in the interval (410) described above with reference to FIG. 4. A second model voltage (724) of the battery may be calculated using the battery model. A second model OCV (726) of the battery may be calculated using the battery model. The model overvoltage may be determined as the value obtained by subtracting the second model voltage (724) from the second model OCV (726). The second OCV (728) may be determined as the sum of the model overvoltage and the second sensing voltage (722).

[0127] According to one embodiment, a second SOC corresponding to a second OCV (728) can be determined. For example, a second SOC corresponding to a second OCV can be determined based on a predefined LUT for the relationship between the battery's OCV curve (703) and SOC.

[0128] According to one embodiment, the rate of change of capacity of the positive active material can be calculated as a value of a degradation parameter based on the value of the current accumulated in the battery during the interval between time point a and time point b (or between the first SOC and the second SOC).

[0130] FIG. 8a illustrates a method for determining a first OCV for calculating an electrode balance shift according to one example.

[0131] The x-axis of the illustrated graph can correspond to the time during which the battery discharge proceeds or the amount of decrease in SOC.

[0132] According to one embodiment, at time c, a first value of the model parameter may correspond to a third threshold value set for the model parameter. For example, the value of the cathode ion concentration determined based on the sensing data may correspond to the third threshold value (e.g., 0.3) at time c. Time c may be included in the interval (420) described above with reference to FIG. 4.

[0133] In addition to the condition regarding the value of the cathode ion concentration, time c can be determined if the condition regarding the value of the anode ion concentration is satisfied. For example, if the value of the anode ion concentration is greater than or equal to a specific threshold (e.g., 0.75), the additional condition may be satisfied.

[0134] The third model voltage (814) of the battery can be calculated using the battery model. The third model OCV (816) of the battery can be calculated using the battery model. The model overvoltage can be determined by subtracting the third model voltage (814) from the third model OCV (816). The third OCV (818) can be determined as the sum of the model overvoltage and the third sensing voltage (812).

[0135] According to one embodiment, a third SOC corresponding to a third OCV (818) can be determined. For example, a third SOC corresponding to a third OCV can be determined based on a predefined LUT for the relationship between the battery's OCV curve (803) and SOC.

[0137] FIG. 8b illustrates a method for determining a second OCV for calculating an electrode balance shift according to one example.

[0138] The x-axis of the illustrated graph can correspond to the time during which the battery discharge proceeds or the amount of decrease in SOC.

[0139] According to one embodiment, at time d, a fourth value of the model parameter may correspond to a fourth threshold value set for the model parameter. For example, the value of the cathode ion concentration determined based on the sensing data may correspond to the fourth threshold value (e.g., 0.1) at time d. Time d may be included in the interval (420) described above with reference to FIG. 4.

[0140] According to one embodiment, the point in time d can be determined as the point in time when the current SOC has decreased by, for example, 10% or more compared to the third SOC determined with reference to FIG. 8.

[0141] The fourth model voltage (824) of the battery can be calculated using the battery model. The fourth model OCV (826) of the battery can be calculated using the battery model. The model overvoltage can be determined by subtracting the fourth model voltage (824) from the fourth model OCV (826). The fourth OCV (828) can be determined as the sum of the model overvoltage and the fourth sensing voltage (822).

[0142] According to one embodiment, a fourth SOC corresponding to a fourth OCV (828) can be determined. For example, a fourth SOC corresponding to a fourth OCV can be determined based on a predefined LUT for the relationship between the battery's OCV curve (803) and SOC.

[0143] According to one embodiment, the electrode balance shift can be calculated as a value of a degradation parameter based on the current accumulated in the battery during the interval between time c and time d (or between the third SOC and the fourth SOC).

[0145] FIG. 9 is a flowchart of a method for determining the second OCV of a battery according to one example.

[0146] According to one embodiment, operations 910 to 950 of FIG. 9 may be associated with operation 535 described above with reference to FIG. 5. For example, operation 535 may include operations 910 to 950.

[0147] Operations 910 to 950 may be performed by an electronic device (e.g., the battery state estimation device (120) of FIG. 1 or the electronic device (200) of FIG. 2). For example, the electronic device may include at least one processor (e.g., the processor (220) of FIG. 2) and a memory (e.g., the memory (230) of FIG. 2).

[0148] In operation 910, the electronic device may acquire second sensing data measured from one or more sensors connected to the battery. For example, the second sensing data may include voltage data, current data and / or temperature data.

[0149] In operation 920, the electronic device can determine a second value of a model parameter of a battery model that estimates the state of the battery based on second sensing data. The description of the method for determining the second value of the model parameter may be replaced with the description of operation 510 for determining the first value of the model parameter.

[0150] In operation 930, the electronic device can determine whether a second value of the model parameter corresponds to a second threshold value set for the model parameter. For example, the model parameter may be a cathode ion concentration.

[0151] The second threshold value may correspond to the end point of the section (410) described above with reference to FIG. 4. For example, if the model parameter is the negative ion concentration and the degradation parameter is the rate of change of the capacity of the positive active material, the second threshold value set for the model parameter may be a value between 0.65 and 0.40.

[0152] The second threshold value may correspond to the end point of the section (420) described above with reference to FIG. 4. For example, if the model parameter is cathode ion concentration and the degradation parameter is electrode balance shift, the second threshold value set for the model parameter may be a value between 0.20 and 0.05.

[0153] If the second value of the model parameter does not correspond to the second threshold value set for the model parameter, operations 910 to 930 may be performed repeatedly.

[0154] In operation 940, if the second value of the model parameter corresponds to a second threshold value set for the model parameter, the electronic device can determine the second model overvoltage (or, overpotential) of the battery using the battery model.

[0155] In operation 950, the electronic device can determine the second OCV of the battery based on the second sensing voltage of the battery and the second model overvoltage among the second sensing data. For example, the sum of the second sensing voltage of the battery and the second model overvoltage can be determined as the second OCV.

[0157] FIG. 10a illustrates a fresh OCV curve that appears when the battery is in a fresh state, according to one example, and an adjusted OCV curve determined based on the SOCs determined during the use of the battery.

[0158] The x-axis of the illustrated graph can correspond to the time during which the battery discharge proceeds or the amount of decrease in SOC.

[0159] According to one embodiment, the OCV curve of a battery can be adjusted as the value of a degradation parameter is updated. For example, the OCV of a battery in a fresh state fresh The OCV of the battery in a degraded state, curve (1010). new It can be changed to a curve (1020). OCV of a fresh battery fresh Compared to curve (1010), the OCV of the degraded battery new The curve (1020) may have a lower voltage for the same discharge point. As the voltage of the OCV decreases overall, the SOH of the battery may decrease.

[0161] FIG. 10b illustrates the initial battery capacity determined based on a fresh OCV curve and the current battery capacity determined based on an adjusted OCV curve, according to one example.

[0162] According to one embodiment, the OCV of a battery in a fresh state fresh A standard discharge overvoltage curve (1012) can be calculated for the curve (1010). For example, the standard discharge overvoltage curve (1012) is OCV fresh There may be a difference △V between the curve (1010) and the voltage drop caused by the cell's initial resistance. The voltage drop caused by the initial resistance can be calculated as the product of the current and the initial resistance.

[0163] Initial battery capacity Q initial The standard discharge overvoltage curve (1012) is a preset threshold voltage V from the start of the discharge. th It can be the accumulated charge discharged up to time e when it is reached. For example, the critical voltage V th The voltage may be 3.3V and is not limited to the described embodiments.

[0164] According to one embodiment, the OCV of a battery in a degraded state newA standard discharge overvoltage curve (1022) can be calculated for the curve (1020). For example, the first standard discharge overvoltage curve (1022) is OCV new There may be a difference △V1 between the curve (1020) and the voltage drop caused by the cell initial resistance. The voltage drop caused by the initial resistance can be calculated as the product of the current and the initial resistance.

[0165] A second standard overvoltage curve (1024) can be calculated based on a first standard discharge overvoltage curve (1022). For example, the second standard discharge overvoltage curve (1024) may have a difference △V2 from the first standard discharge overvoltage curve (1022) by the voltage drop caused by the SEI resistance. The SEI resistance may be determined based on a battery model. As the value of the degradation parameter is updated, the SEI resistance determined based on the battery model may be increased.

[0166] Current battery capacity Q new The second standard discharge overvoltage curve (1024) is a preset threshold voltage V from the start of the discharge. th It may be the accumulated charge discharged up to the point f when it is reached.

[0167] According to one embodiment, as state information of the battery, SOH is the initial battery capacity Q initial and current battery capacity Q new It can be calculated based on [Equation 4]. For example, SOH can be calculated using the aforementioned [Equation 4].

[0169] FIG. 11 is a drawing for explaining a vehicle according to one example.

[0170] Referring to FIG. 11, the vehicle (1100) includes a battery pack (1110). The vehicle (1100) may be a vehicle that uses the battery pack (1110) as a power source. The vehicle (1100) may be, for example, an electric vehicle or a hybrid vehicle.

[0171] The battery pack (1110) includes a battery management system (BMS) and battery cells (or battery modules). The BMS can monitor whether an abnormality has occurred in the battery pack (1110) and can prevent the battery pack (1110) from being overcharged or overdischarged. Additionally, the BMS can perform thermal control on the battery pack (1110) if the temperature of the battery pack (1110) exceeds a first temperature (e.g., 40°C) or is below a second temperature (e.g., -10°C). Additionally, the BMS can perform cell balancing to ensure that the charge state between the battery cells within the battery pack (1110) becomes equal.

[0172] According to one embodiment, the vehicle (1100) includes a battery state estimation device (e.g., the battery state estimation device (120) of FIG. 1 or the electronic device (200) of FIG. 2). The battery state estimation device can determine state information of the battery pack (1110) (or battery cells within the battery pack (1110).

[0174] FIG. 12 is a drawing for explaining a mobile terminal according to one example.

[0175] Referring to FIG. 12, a mobile terminal (1200) includes a battery pack (1210). The mobile terminal (1200) may be a device that uses the battery pack (1210) as a power source. The mobile terminal (1200) may be a portable terminal, for example, a smartphone. The battery pack (1210) includes a BMS and battery cells (or battery modules).

[0176] According to one embodiment, the mobile terminal (1200) includes a battery state estimation device (e.g., the battery state estimation device (120) of FIG. 1 or the electronic device (200) of FIG. 2). The battery state estimation device can determine state information of a battery pack (1210) (or battery cells within the battery pack (1210)).

[0177] According to one embodiment, a mobile terminal (1200) may include a display, a battery that supplies power to the display, at least one processor including a processing circuit, and a memory including one or more storage media that stores instructions. For example, the operations 505 to 555 described above with reference to FIG. 5 may be performed by the mobile terminal (1200) by the instructions.

[0179] FIG. 13 is a drawing for explaining an electronic device according to one example.

[0180] Referring to FIG. 13, an electronic device (1310) (e.g., the electronic device (200) of FIG. 2) includes a battery (1311) and a battery state estimation device (1312). The electronic device (1310) may be a mobile terminal such as a smartphone, laptop, tablet PC, or wearable device, but is not limited thereto. The battery (1311) can be charged by receiving power from a power source (1320). The battery state estimation device (1312) can determine state information of the battery (1311).

[0182] FIG. 14 is a flowchart of a method for determining battery status according to one embodiment.

[0183] The operations 1410 to 1460 of FIG. 14 may be performed by an electronic device (e.g., the battery state estimation device (120) of FIG. 1 or the electronic device (200) of FIG. 2). For example, the electronic device may include at least one processor (e.g., the processor (220) of FIG. 2) and a memory (e.g., the memory (230) of FIG. 2).

[0184] In operation 1410, the electronic device may acquire sensing data measured from one or more sensors connected to the battery. The sensing data acquired in operation 1410 may be named first sensing data to distinguish it from other sensing data. The description of operation 1410 may be replaced by the description of operation 505 described above with reference to FIG. 5.

[0185] In operation 1420, the electronic device may determine a first SOC of the battery using the battery model and sensing data when the first value of the model parameter corresponds to a first threshold value. For example, the electronic device may determine a first value of the model parameter of the battery model that estimates the state of the battery based on the first sensing data, and determine whether the determined first value corresponds to a first threshold value. The first threshold value may be a preset value for the model parameter. The description of operation 1420 may be replaced by the description of operations 510 and 515 described above with reference to FIG. 5. For example, operation 1420 may include operations 510 and 515.

[0186] According to one embodiment, operation 1420 may include operations 610 to 630 described above with reference to FIG. 6. For example, the electronic device may determine a first OCV of the battery based on a first sensing voltage of the battery and a first model overvoltage among the first sensing data, and determine a first SOC corresponding to the first OCV.

[0187] In operation 1430, the electronic device may determine a second SOC of the battery using the battery model and sensing data when the second value of the model parameter corresponds to a second threshold value. The sensing data described in operation 1430 may be named second sensing data to distinguish it from other sensing data. For example, the electronic device may determine a second value of the model parameter of the battery model that estimates the state of the battery based on the second sensing data, and determine whether the determined second value corresponds to a second threshold value. The second threshold value may be a preset value for the model parameter. The description of operation 1430 may be replaced by the description of operations 535 and 540 described above with reference to FIG. 5. For example, operation 1430 may include operations 535 and 540.

[0188] According to one embodiment, operation 1430 may include operations 610 to 630 described above with reference to FIG. 6. For example, the electronic device may determine a second OCV of the battery based on a second sensing voltage and a second model overvoltage of the battery among the second sensing data, and determine a second SOC corresponding to the second OCV.

[0189] In operation 1440, the electronic device can determine the calculated value of the current consumed from the battery during the interval between the first SOC and the second SOC. The description of operation 1440 may be replaced with the description of operation 545 described above with reference to FIG. 5.

[0190] In operation 1450, the electronic device can update the value of the degradation parameter of the battery model based on the first SOC, the second SOC, and the current integration value. The description of operation 1450 may be replaced with the description of operation 550 described above with reference to FIG. 5.

[0191] In operation 1460, the electronic device can determine the state of the battery using a battery model in which the values ​​of the degradation parameters have been updated. The description of operation 1460 may be replaced with the description of operation 555 described above with reference to FIG. 5.

[0193] The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., either individually or in combination. The program instructions recorded on the medium may be those specifically designed and configured for the embodiment, or they may be those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

[0194] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or command the processing unit independently or collectively. Software and / or data may be permanently or temporarily embodied in any type of machine, component, physical device, virtual equipment, computer storage medium or device, or transmitted signal wave so as to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

[0195] Although the embodiments described above have been explained with reference to limited drawings, those skilled in the art can apply various technical modifications and variations based on the above. For example, appropriate results can be achieved even if the described techniques are performed in a different order than described, and / or the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0196] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below.

Claims

Claim 1 A battery state determination method performed by an electronic device, comprising: determining a first value of a model parameter of a battery model that estimates the state of the battery based on first sensing data measured from one or more sensors connected to the battery of the electronic device; determining a first state of charge (SOC) of the battery using the battery model and the first sensing data when the first value of the model parameter corresponds to a first threshold value; determining a second SOC when the second value of the model parameter corresponds to a second threshold value set for the model parameter; determining an integrated current value consumed in the battery during an interval between the first SOC and the second SOC; updating a value of a degradation parameter of the battery model based on the first SOC, the second SOC, and the integrated current value; and determining the state of the battery using the battery model in which the value of the degradation parameter has been updated. Claim 2 A battery state determination method according to claim 1, further comprising: an operation of determining a first model voltage of the battery using the battery model; an operation of determining a first model OCV of the battery using the battery model; and an operation of determining the first model overvoltage based on the first model voltage and the first model OCV, wherein the operation of determining the first SOC includes: an operation of determining the first OCV (open circuit voltage) of the battery based on the first sensing voltage of the battery and the first model overvoltage among the first sensing data; and an operation of determining the first SOC corresponding to the first OCV. Claim 3 A battery state determination method according to claim 2, wherein the operation of determining the first SOC corresponding to the first OCV includes the operation of determining the first SOC corresponding to the first OCV using a look-up table (LUT) representing the relationship between the OCV and SOC of the battery. Claim 4 A battery state determination method according to claim 1, wherein the operation of determining the second SOC comprises: acquiring second sensing data measured from one or more sensors connected to the battery; determining a second value of the model parameter based on the second sensing data; determining whether the second value of the model parameter corresponds to a second threshold value set for the model parameter; determining a second model overvoltage of the battery using the battery model when the second value of the model parameter corresponds to the second threshold value; determining a second OCV of the battery based on the second sensing voltage of the battery and the second model overvoltage among the second sensing data; and determining the second SOC corresponding to the second OCV. Claim 5 A method for determining the state of a battery according to claim 1, wherein the state of the battery includes the State of Health (SOH) of the battery. Claim 6 A method for determining battery state according to claim 1, wherein the model parameter is the cathode ion concentration. Claim 7 A battery state determination method according to claim 6, wherein the first threshold value set for the model parameter, which is the cathode ion concentration, is a value between 0.85 and 0.

65. Claim 8 A battery state determination method according to claim 7, wherein the second threshold value set for the model parameter, which is the cathode ion concentration, is a value between 0.65 and 0.

40. Claim 9 A method for determining battery state according to claim 7, wherein the degradation parameter is the rate of change of capacity of the positive active material. Claim 10 A battery state determination method according to claim 6, wherein the first threshold value set for the model parameter, which is the cathode ion concentration, is a value between 0.40 and 0.

20. Claim 11 A battery state determination method according to claim 10, wherein the second threshold value set for the model parameter, which is the cathode ion concentration, is a value between 0.20 and 0.

05. Claim 12 In item 10, the above degradation parameter is an electrode balance shift, a method for determining battery state. Claim 13 In claim 1, the electronic device is a mobile terminal, a method for determining battery status. Claim 14 A computer-readable recording medium storing a computer program that executes the method of any one of paragraphs 1 through 13. Claim 15 An electronic device comprising: at least one processor including processing circuitry; and a memory including one or more storage media for storing instructions, wherein when the instructions are executed individually or collectively by the at least one processor, the electronic device is configured to: determine a first value of a model parameter of a battery model that estimates the state of the battery based on first sensing data measured from one or more sensors connected to the battery of the electronic device; determine a first state of charge (SOC) of the battery using the battery model and the first sensing data when the first value of the model parameter corresponds to a first threshold value; determine a second SOC when the second value of the model parameter corresponds to a second threshold value set for the model parameter; determine an integrated current value consumed in the battery during the interval between the first SOC and the second SOC; update a value of a degradation parameter of the battery model based on the first SOC, the second SOC and the integrated current value; and determine the state of the battery using the battery model in which the value of the degradation parameter has been updated. Claim 16 A mobile terminal comprises: a display; a battery that supplies power to the display; and at least one processor including processing circuitry. The mobile terminal comprises a memory including one or more storage media for storing instructions, and when the instructions are executed individually or collectively by the at least one processor, the mobile terminal: acquires first sensing data measured from one or more sensors connected to the battery; determines a first value of a model parameter of a battery model that estimates the state of the battery based on the first sensing data; determines whether the first value of the model parameter corresponds to a first threshold value set for the model parameter; if the first value of the model parameter corresponds to the first threshold value, determines a first model overvoltage of the battery using the battery model; determines a first OCV (open circuit voltage) of the battery based on the first sensing voltage of the battery and the first model overvoltage among the first sensing data; determines a first SOC (state of charge) corresponding to the first OCV; and determines a second OCV of the battery based on a second model overvoltage of the battery determined as the second value of the model parameter corresponds to a second threshold value set for the model parameter. A mobile terminal that determines, determines a second SOC corresponding to the second OCV, determines an integrated current value consumed in the battery during the interval between the first SOC and the second SOC, updates the value of a degradation parameter of the battery model based on the first SOC, the second SOC and the integrated current value, and determines the state of the battery using the battery model in which the value of the degradation parameter has been updated. Claim 17 In claim 16, when the above instructions are executed individually or collectively by the at least one processor, the mobile terminal is configured to: determine a first model voltage of the battery using the battery model, determine a first model OCV of the battery using the battery model, and determine a first model overvoltage based on the first model voltage and the first model OCV. Claim 18 In claim 16, when the above instructions are executed individually or collectively by the at least one processor, the mobile terminal is configured to: acquire second sensing data measured from the one or more sensors connected to the battery; determine a second value of the model parameter based on the second sensing data; determine whether the second value of the model parameter corresponds to a second threshold value set for the model parameter; if the second value of the model parameter corresponds to the second threshold value, determine a second model overvoltage of the battery using the battery model; and determine a second OCV of the battery based on the second sensing voltage of the battery and the second model overvoltage among the second sensing data. Claim 19 In Clause 16, the above model parameter is a cathode ion concentration, a mobile terminal. Claim 20 In claim 16, the above degradation parameter is a rate of change in the capacity of the positive active material or an electrode balance shift, a mobile terminal.

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