Method estimating a state of battery and electronic appatatus performing the method

Abstract

A battery state estimation method and an electronic device are disclosed. One embodiment determines an estimated voltage of a battery and a surface concentration of each electrode of the battery through a battery model, obtains a sensing voltage of the battery using a voltage sensor, determines a voltage difference between the obtained sensing voltage and the determined estimated voltage, determines a state change amount of the battery based on the determined voltage difference and each determined surface concentration, updates the battery model based on the determined state change amount, and determines state information of the battery based on the updated battery model.

Description

Technology Field

[0001] The following disclosure relates to a method for estimating battery state and an electronic device for performing the same. Background Technology

[0002] There are various methods for estimating the state of a battery. For example, the state of a battery can be estimated by integrating the current of the battery or by using a battery model (e.g., an electrical circuit model or an electrochemical model). A related prior art is Korean Patent Publication No. 10-2023-0075033 (Title of Invention: Electronic device for estimating battery state and method of operation thereof; Applicant: Samsung Electronics Co., Ltd.). means of solving the problem

[0003] According to one embodiment, a method for estimating the state of a battery of an electronic device comprises: determining an estimated voltage of the battery and a surface concentration of each electrode of the battery through a battery model; obtaining a sensing voltage of the battery using a voltage sensor; determining a voltage difference between the obtained sensing voltage and the determined estimated voltage; determining a state variation of the battery based on the determined voltage difference and each determined surface concentration; updating the battery model based on the determined state variation; and determining state information of the battery based on the updated battery model.

[0004] The step of determining the amount of change in state may include: determining a first open circuit potential (OCP) of each of the electrodes using each of the determined surface concentrations; determining a first open circuit voltage (OCV) of the battery using each of the determined first OCPs; correcting each of the determined surface concentrations based on the amount of change in state; determining a second OCP of each of the electrodes using each of the corrected surface concentrations; determining a second OCV of the battery using each of the determined second OCPs; and determining the amount of change in state using the determined first OCV, the determined second OCV, the amount of change in state, and the determined voltage difference.

[0005] The step of determining the first OCP of each of the electrodes may include determining the first OCP of each of the electrodes using each OCP table representing the relationship between the stoichiometric concentration and OCP of each of the electrodes and each determined surface concentration.

[0006] The step of determining the state change amount using the determined first OCV, the determined second OCV, the initial state change amount, and the determined voltage difference may include: a step of determining the difference value between the determined second OCV and the determined first OCV; and a step of determining the state change amount by applying the ratio between the determined difference value and the determined voltage difference to the initial state change amount.

[0007] The step of correcting each determined surface concentration may include: a step of determining each correction value for correcting each determined surface concentration using a predetermined value for each of the electrodes and the initial state change amount; and a step of correcting each determined surface concentration based on each determined correction value.

[0008] The step of determining the amount of state change may include: determining the OCP of each of the electrodes using the determined surface concentration; determining the OCV of the battery using the determined OCP; and determining the optimal value of the amount of state change by performing an optimization operation to optimize the amount of state change based on the determined voltage difference, the determined surface concentration, and the determined OCV.

[0009] The step of determining the optimal value may include the step of performing the optimization operation by setting the voltage difference between the OCV considering the state change amount and the determined OCV to be the same as the determined voltage difference.

[0010] The step of determining the amount of change in state may include: obtaining a first ratio value corresponding to the determined surface concentration of the first electrode from a first table representing the relationship between the ratio between the amount of change in concentration of the first electrode and the amount of change in OCP among the electrodes and the concentration of the first electrode; obtaining a second ratio value corresponding to the determined surface concentration of the second electrode from a second table representing the relationship between the ratio between the amount of change in concentration of the second electrode and the amount of change in OCP among the electrodes and the concentration of the second electrode; and determining the amount of change in state using the determined voltage difference, the obtained first ratio value, the obtained second ratio value, and the initial amount of change in state.

[0011] The step of determining the state change amount using the determined voltage difference, the obtained first ratio value, the obtained second ratio value, and the initial state change amount may include: a step of determining a first correction value for correcting the surface concentration of the first electrode by applying the initial state change amount to a predetermined value for the first electrode; a step of determining a first OCP change amount value of the first electrode using the determined first correction value and the obtained first ratio value; a step of determining a second correction value for correcting the surface concentration of the second electrode by applying the initial state change amount to a predetermined value for the second electrode; a step of determining a second OCP change amount value of the second electrode using the determined second correction value and the obtained second ratio value; a step of calculating the sum of the determined first OCP change amount value and the determined second OCP change amount value; and a step of determining the state change amount by applying the ratio between the determined voltage difference and the calculated sum to the initial state change amount.

[0012] The step of updating the battery model may include the step of updating the internal state of the electrochemical model by correcting at least one of the parameters of the battery model based on the determined amount of change in state.

[0013] According to one embodiment, a computer-readable storage medium can record a program for executing the battery state estimation method.

[0014] According to one embodiment, an electronic device includes a battery; a voltage sensor; a memory storing a battery model; and a processor operatively connected to the memory. The processor determines an estimated voltage of the battery and a surface concentration of each electrode of the battery through the battery model, obtains a sensing voltage of the battery using the voltage sensor, determines a voltage difference between the obtained sensing voltage and the determined estimated voltage, determines a state change amount of the battery based on the determined voltage difference and each determined surface concentration, updates the battery model based on the determined state change amount, and determines state information of the battery based on the updated battery model.

[0015] The processor can determine a first open-circuit potential of each of the electrodes using each of the determined surface concentrations, determine a first open-circuit voltage of the battery using each of the determined first OCPs, correct each of the determined surface concentrations based on an initial state change amount, determine a second OCP of each of the electrodes using each of the corrected surface concentrations, determine a second OCV of the battery using each of the determined second OCPs, and determine a state change amount using the determined first OCV, the determined second OCV, the initial state change amount, and the determined voltage difference.

[0016] The processor can determine the first OCP of each of the electrodes using each OCP table representing the relationship between the stoichiometric concentration of each of the electrodes and the OCP, and each determined surface concentration.

[0017] The processor can determine the difference value between the determined second OCV and the determined first OCV, and determine the state change amount by applying the ratio between the determined difference value and the determined voltage difference to the initial state change amount.

[0018] The processor can determine each correction value for correcting each determined surface concentration using a predetermined value for each of the electrodes and the initial state change amount, and correct each determined surface concentration based on each determined correction value.

[0019] The processor can determine the OCP of each of the electrodes using the determined surface concentration, determine the OCV of the battery using the determined OCP, and determine the optimal value of the state change amount by performing an optimization operation to optimize the state change amount based on the determined voltage difference, the determined surface concentration, and the determined OCV.

[0020] The processor can perform the optimization operation by setting the voltage difference between the OCV considering the state change amount and the determined OCV to be the same as the determined voltage difference.

[0021] The processor can obtain a first ratio value corresponding to the determined surface concentration of the first electrode from a first table representing the relationship between the ratio between the concentration change amount of the first electrode among the electrodes and the OCP change amount and the concentration of the first electrode, and obtain a second ratio value corresponding to the determined surface concentration of the second electrode from a second table representing the relationship between the ratio between the concentration change amount of the second electrode among the electrodes and the OCP change amount and the concentration of the second electrode, and can determine the state change amount using the determined voltage difference, the obtained first ratio value, the obtained second ratio value, and the initial state change amount.

[0022] The processor can control the display so that the determined state information is displayed on the display of the electronic device. Brief explanation of the drawing

[0023] FIGS. 1 and FIGS. 2 are drawings for explaining a battery system according to one embodiment. FIG. 3 is a flowchart illustrating a battery state estimation method according to one embodiment. FIGS. 4 and 5 are drawings illustrating an example of determining the amount of change in the state of a battery according to one embodiment. FIG. 6 is a drawing illustrating another example of determining the amount of change in the state of a battery according to one embodiment. FIGS. 7a, FIGS. 7b, and FIGS. 8 are drawings illustrating other examples of determining the amount of state change of a battery according to one embodiment. FIG. 9 is a diagram illustrating an example of determining the initial state change amount of a battery state estimation device according to one embodiment. FIG. 10 is a block diagram illustrating the configuration of a battery state estimation device according to one embodiment. FIG. 11 is a block diagram illustrating an electronic device including a battery state estimation device according to one embodiment. FIG. 12 is a block diagram illustrating a mobile device according to one embodiment. Specific details for implementing the invention

[0024] Specific structural or functional descriptions of the embodiments are disclosed for illustrative purposes only and may be modified and implemented in various forms. Accordingly, actual implementations are not limited to the specific embodiments disclosed, and the scope of this specification includes modifications, equivalents, or substitutions included in the technical concept described by the embodiments.

[0025] Terms such as "first" or "second" may be used to describe various components, but these terms should be interpreted solely for the purpose of distinguishing one component from another. For example, the first component may be named the second component, and similarly, the second component may be named the first component.

[0026] When it is stated that a component is "connected" to another component, it should be understood that it may be directly connected to or joined to that other component, or that there may be other components in between.

[0027] The singular expression includes the plural expression unless the context clearly indicates otherwise. In this specification, terms such as “comprising” or “having” are intended to specify the existence of the described features, numbers, steps, actions, components, parts, or combinations thereof, 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.

[0028] 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. 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 specification.

[0029] Hereinafter, embodiments will be described in detail with reference to the attached drawings. In the description with reference to the attached drawings, identical components are given the same reference numeral regardless of the drawing number, and redundant descriptions thereof will be omitted.

[0031] FIGS. 1 and FIGS. 2 are drawings for explaining a battery system according to one embodiment.

[0032] Referring to FIG. 1, a battery system (100) according to one embodiment includes a battery (110) and a battery state estimation device (120). Although one battery (110) is shown in FIG. 1, this is merely an example, and the battery system (100) may include two or more batteries.

[0033] The battery (110) can be a battery cell, a battery module, or a battery pack.

[0034] The battery state estimation device (120) senses the battery (110) using one or more sensors (e.g., at least one of a voltage sensor, a current sensor, or a temperature sensor). Alternatively, the battery state estimation device (120) can collect sensing data for each battery (100). The sensing data may include, for example, battery (110) voltage data, current data, and / or temperature data.

[0035] The battery state estimation device (120) can determine (or estimate) state information of the battery (110) based on sensing data. The state information of the battery (110) may include, for example, State of Charge (SOC), State of Health (SOH), and / or abnormality state information. The battery model used when estimating state information may include an electrochemical model. This is explained through FIG. 2.

[0036] Referring to FIG. 2, an example of estimating state information using a battery model according to one embodiment is illustrated.

[0037] The battery state estimation device (120) can estimate state information of the battery (110) using a battery model (e.g., an electrochemical model). The electrochemical model is a model that estimates state information of the battery by modeling internal physical phenomena such as the battery's potential and ion concentration distribution.

[0038] The battery state estimation device (120) can determine the voltage difference between the sensing voltage of the battery (110) measured by the sensor and the estimated voltage of the battery (110) estimated by the battery model. The battery state estimation device (120) can determine the amount of state change of the battery (110) using the determined voltage difference (dV or △V). The amount of state change may include, for example, the amount of SOC change (d_SOC). The battery state estimation device (120) can update the internal state of the battery model based on the amount of state change of the battery (110). The battery state estimation device (120) can determine (or estimate) the state information of the battery (110) based on the updated internal state of the battery model. In this way, through a feedback structure that determines the amount of state change of the battery (110) so as to minimize the voltage difference between the sensing voltage of the battery (110) and the estimated voltage estimated by the battery model, and updates the internal state of the battery model through the determined amount of state change, the battery state estimation device (120) can determine or estimate the state information of the battery with high accuracy without increasing the model complexity (e.g., the complexity of the battery model) and the amount of computation of the battery model.

[0040] FIG. 3 is a flowchart illustrating a battery state estimation method according to one embodiment.

[0041] Referring to FIG. 3, in step 310, the battery state estimation device (120) estimates the voltage (V) of the battery (110) through the battery model. est Determines the surface concentration of each of the electrodes of the battery (110). The surface concentration of each of the electrodes may represent, for example, the concentration (or ion concentration) of the active material on the surface of each of the electrodes of the battery (110). The unit of concentration is, for example, mol / m² 3 It may be, but is not limited to. Estimated voltage (V) of the battery (110) est) is calculated by the battery state estimation device (120) through the battery model, so it can be expressed as the calculated voltage of the battery (110).

[0042] In step 320, the battery state estimation device (120) senses the sensing voltage (V) of the battery (110). sen ) obtains. For example, the battery state estimation device (120) uses a voltage sensor to obtain the sensed voltage (V) of the battery (110). sen You can obtain ).

[0043] In step 330, the battery state estimation device (120) senses the sensing voltage (V) of the battery (110). sen Estimated voltage (V) of ) and battery (110) est Determines the voltage difference (dV or △V) between ). The voltage difference (dV or △V) is, for example, "sensing voltage (V sen )―Estimated voltage (V est )" can be. Depending on the implementation, the voltage difference is "estimated voltage (V est )―Sensing voltage(V sen It could be ”

[0044] In step 340, the battery state estimation device (120) determines the amount of change in state (d_SOC) of the battery (110) based on the voltage difference (dV) and the surface concentration of each electrode.

[0045] As will be described later through FIGS. 4 and 5, according to one embodiment, the battery state estimation device (120) can determine the open circuit potential (OCP) (hereinafter referred to as "first OCP") of each electrode of the battery (110) using the surface concentration of each electrode (e.g., the OCP value corresponding to the surface concentration of each electrode described through FIGS. 4 and 5). In other words, the battery state estimation device (120) can determine the first OCP of the cathode of the battery (110) and the first OCP of the anode. The battery state estimation device (120) can determine the open circuit voltage (OCV) (hereinafter referred to as "first OCV") of the battery (110) (e.g., OCV1 described later through FIGS. 4 and 5) using each determined first OCP. The battery state estimation device (120) can correct the surface concentration of each electrode of the battery (110) based on the initial state change amount (d_SOC_0). The battery state estimation device (120) can determine the OCP of each electrode (hereinafter referred to as "second OCP") (e.g., the OCP value corresponding to the shifted (or corrected) surface concentration (X1+dX) of each electrode described through FIGS. 4 and FIGS. 5) using the corrected surface concentration. In other words, the battery state estimation device (120) can determine the second OCP of the positive electrode of the battery (110) and the second OCP of the negative electrode. The battery state estimation device (120) can determine the OCV of the battery (110) (hereinafter referred to as "second OCV") (e.g., OCV2 described later through FIGS. 4 or OCV#3 described later through FIGS. 5) using the determined second OCP. The battery state estimation device (120) can determine the state change amount (d_SOC) using the determined first OCV, the determined second OCV, the initial state change amount (d_SOC_0), and the determined voltage difference (dV).

[0046] As will be explained in detail through FIG. 6, according to another embodiment, the battery state estimation device (120) can determine the optimal value of the state change amount by performing an optimization operation to optimize the state change amount based on the determined voltage difference (dV), the surface concentration of each electrode, and the determined first OCV when the first OCV of the battery (110) is determined. This will be described later through FIG. 6.

[0047] As will be explained in detail through FIGS. 7a, 7b, and FIGS. 8, according to another embodiment, the battery state estimation device (120) can obtain a first ratio value corresponding to the surface concentration of the positive electrode of the battery (110) from a first table representing the relationship between the ratio (dOCP / dY) between the change in concentration of the positive electrode (dY) and the change in OCP (dOCP) among the electrodes of the battery (110) and the concentration of the positive electrode (e.g., stoichiometric concentration). The battery state estimation device (120) can obtain a second ratio value corresponding to the surface concentration of the negative electrode from a second table representing the relationship between the ratio (dOCP / dX) between the change in concentration of the negative electrode of the battery (110) and the change in OCP (e.g., stoichiometric concentration). The battery state estimation device (120) can determine the state change amount (d_SOC) using the determined voltage difference (dV), the obtained first ratio value, the obtained second ratio value, and the initial state change amount.

[0048] In step 350, the battery state estimation device (120) updates the battery model based on the determined amount of state change. For example, the battery state estimation device (120) can update the battery model by correcting at least one of the parameters of the electrochemical model (e.g., ion concentration distribution within active material particles and / or ion concentration distribution within electrodes) based on the determined amount of state change.

[0049] In step 360, the battery state estimation device (120) determines state information (e.g., SOC, SOH, etc.) of the battery (110) based on the updated battery model.

[0051] FIGS. 4 and 5 are drawings illustrating an example of determining the amount of change in the state of a battery according to one embodiment.

[0052] In FIGS. 4 and FIG. 5, a graph (410) corresponding to a first OCP table and a graph (420) corresponding to a second OCP table are illustrated. The first OCP table may correspond to an OCP table representing, for example, the relationship between the stoichiometric concentration of the positive electrode of the battery (110) and OCP. The graph (410) may represent a curve (or graph) of OCP according to the stoichiometric concentration of the positive electrode of the battery (110). The second OCP table may correspond to an OCP table representing, for example, the relationship between the stoichiometric concentration of the negative electrode of the battery (110) and OCP. The graph (420) may represent a curve (or graph) of OCP according to the stoichiometric concentration of the negative electrode of the battery (110).

[0053] Unlike SOC, which is a relative value that can vary from 0 to 100% depending on the application, stoichiometric concentration can have an absolute value.

[0054] In the example illustrated in FIG. 4, the battery state estimation device (120) through the battery model the surface concentration of each of the electrodes of the battery (110), the estimated voltage (V) of the battery (110) est The SOC of the battery (110) (hereinafter referred to as "SOC1" in FIG. 4) can be determined.

[0055] The battery state estimation device (120) is the sensing voltage (V) of the battery (110). sen Estimated voltage (V) of ) and battery (110) est The voltage difference (dV) between ) can be determined. For example, the estimated voltage (Vest ) is the sensing voltage (V sen It can be 300mV smaller than ). The battery state estimation device (120) is "sensing voltage (V sen )―Estimated voltage (V est According to ,” the voltage difference (dV) can be calculated as 300mV. A positive voltage difference (dV) (e.g., 300mV) may mean that the battery model has determined SOC1 to be smaller than the actual SOC of the battery (110) (e.g., SOC of the battery (110) with various errors, such as sensor errors and battery model errors, excluded) by the internal state of the battery model (e.g., at least one parameter). The battery state estimation device (120) may perform corrections (e.g., surface concentration correction, correction of the internal state of the battery model, etc.) so that the SOC to be subsequently determined by the battery model can match the actual SOC of the battery (110) (or so that the battery model can subsequently determine a higher SOC).

[0056] In the example illustrated in FIG. 4, the surface concentration of the positive electrode of the battery (110) may be Y1, and the surface concentration of the negative electrode of the battery (110) may be X1.

[0057] The battery state estimation device (120) can obtain an OCP value (e.g., 3.95V) corresponding to the surface concentration (Y1) of the positive electrode from the first OCP table (or graph (410)). The battery state estimation device (120) can obtain an OCP value (e.g., 0.17V) corresponding to the surface concentration (X1) of the negative electrode from the second OCP table (or graph (420)).

[0058] The battery state estimation device (120) can calculate a difference value (e.g., 3.78V) between an OCP value (e.g., 3.95V) and an OCP value (e.g., 0.17V). The battery state estimation device (120) can determine the calculated difference value (e.g., 3.78V) as the OCV1 of the battery (110). OCV1 may correspond, for example, to the OCV of the battery (110) at SOC1.

[0059] The battery state estimation device (120) can determine the concentration shift amount (or concentration change amount) of each electrode (e.g., dY (411) and dX (421) in FIG. 4). The concentration shift amount (or concentration change amount) (dY) (411) of the positive electrode can indicate, for example, how much the surface concentration (Y1) of the positive electrode should shift (or how much it should change) on the graph (410). The concentration shift amount (or concentration change amount) (dX) (421) of the negative electrode can indicate, for example, how much the surface concentration (X1) of the negative electrode should shift (or how much it should change) on the graph (420). Since the surface concentration of each electrode can be corrected by the concentration shift amount (or concentration change amount) of each electrode, the concentration shift amount can be expressed as a correction value (or concentration correction amount). The correction value (or concentration correction amount) of each electrode can indicate how much the surface concentration of each electrode should be corrected.

[0060] The battery state estimation device (120) can determine a concentration shift amount (or correction value) (dY) (411) to correct the surface concentration (Y1) of the positive electrode based on the initial state change amount (d_SOC_0). The battery state estimation device (120) can determine a concentration shift amount (or correction value) (dX) (421) to correct the surface concentration (X1) of the negative electrode based on the initial state change amount (d_SOC_0). The initial state change amount (d_SOC_0) may have a fixed value, for example, but is not limited thereto. As will be described later with reference to FIG. 9, the battery state estimation device (120) can determine the initial state change amount (d_SOC_0) through the voltage difference (dV) and the OCV-SOC table (or OCV-SOC graph).

[0061] For example, the battery state estimation device (120) can determine dY (411) (e.g., dY = d_SOC_0 × d_SOC_CA) using a predetermined value (d_SOC_CA) and an initial state change amount (d_SOC_0) for the positive electrode of the battery (110). The battery state estimation device (120) can determine dX (421) (e.g., dX = d_SOC_0 × d_SOC_AN) using a predetermined value (d_SOC_AN) and an initial state change amount (d_SOC_0) for the negative electrode of the battery (110). The voltage difference (dV) can be positive, and as will be explained below, d_SOC_CA can be negative, and d_SOC_AN can be positive. As a result, "dY (411) < 0" and "dX (421) > 0". dY (411) may be in the direction of decreasing anode concentration (e.g., surface concentration or stoichiometric concentration of the anode), and dX (421) may be in the direction of increasing cathode concentration (e.g., surface concentration or stoichiometric concentration of the cathode).

[0062] A predetermined value (d_SOC_CA) for the anode may represent, for example, the difference between the anode concentration corresponding to SOC=100% and the anode concentration corresponding to SOC=0%. For example, the anode concentration corresponding to SOC=100% may be 0.3 and the anode concentration corresponding to SOC=0% may be 0.9. In this case, the predetermined value (d_SOC_CA) for the anode may be -0.6.

[0063] A predetermined value (d_SOC_AN) for the cathode may represent, for example, the difference between the cathode concentration corresponding to SOC=100% and the cathode concentration corresponding to SOC=0%. For example, the cathode concentration corresponding to SOC=100% may be 0.9 and the cathode concentration corresponding to SOC=0% may be 0.01. In this case, the predetermined value (d_SOC_AN) for the cathode may be 0.89.

[0064] The battery state estimation device (120) can correct the surface concentration (Y1) of the positive electrode through dY (411). The corrected surface concentration (Y1+dY) may correspond to a position on the graph (410) where the surface concentration (Y1) is shifted by dY (411). The corrected surface concentration (Y1+dY) may be smaller than the surface concentration (Y1). The battery state estimation device (120) can obtain an OCP value (e.g., 4.1V) corresponding to the corrected (or shifted) surface concentration (Y1+dY) of the positive electrode from the first OCP table (or graph (410)). The battery state estimation device (120) can correct the surface concentration (X1) of the negative electrode through dX (421). The corrected surface concentration (X1+dX) may correspond to a position on the graph (420) where the surface concentration (X1) is shifted by dX (421). The corrected surface concentration (X1+dX) may be greater than the surface concentration (X1). The battery state estimation device (120) can obtain an OCP value (e.g., 0.13V) corresponding to the corrected (or shifted) surface concentration (X1+dX) of the negative electrode in the second OCP table (or graph (420)).

[0065] The battery state estimation device (120) can calculate a difference value (e.g., 3.97V) between an OCP value (e.g., 4.1V) corresponding to the corrected surface concentration of the positive electrode and an OCP value (e.g., 0.13V) corresponding to the corrected surface concentration of the negative electrode. The battery state estimation device (120) can determine the difference value (e.g., 3.97V) as the OCV2 of the battery (110). Since the surface concentration of each electrode can be corrected based on the initial state change amount (d_SOC_0), the OCV2 of the battery (110) may correspond, for example, to the OCV of the battery (110) corrected based on the initial state change amount (d_SOC_0). The OCV2 may correspond to the OCV of the battery (110) at an SOC (e.g., SOC1+d_SOC_0) where the initial state change amount is taken into account.

[0066] The battery state estimation device (120) can determine the amount of change in state (or amount of state error) (d_SOC) of the battery (110) using the initial amount of change in state (d_SOC_0), the OCV1 of the battery (110), the OCV2 of the battery (110), and the voltage difference (dV). For example, the battery state estimation device (120) can determine the amount of change in state (d_SOC) of the battery (110) through the following mathematical formula 1.

[0067]

[0068] In one embodiment, the absolute value of the OCV difference and / or dV of the above mathematical formula 1 may be applied.

[0069] The ratio between d_SOC_0 and d_SOC may be the same as the ratio between the OCV difference (e.g., OCV2―OCV1 = 3.97V―3.78V = 0.19V) and the voltage difference (dV). If d_SOC_0 is, for example, 3%, then d_SOC may be "3% × 0.3 / 0.19 = 4.73%". In other words, the battery state estimation device (120) can determine d_SOC as 4.73% by applying d_SOC_0 to the ratio between the OCV difference and the voltage difference (dV). As described above, the battery state estimation device (120) can update the battery model based on the amount of state change (d_SOC) (e.g., 4.73%) and can determine the state information (e.g., SOC) of the battery (110) through the updated battery model. Accordingly, the battery state estimation device (120) can determine high-accuracy state information.

[0070] Unlike the example shown in FIG. 4, in the example shown in FIG. 5, the estimated voltage (V est ) is the sensing voltage (V sen It can be greater than ). Referring to FIG. 5 below, the estimated voltage (V est ) is the sensing voltage (V sen An example is described in which the battery state estimation device (120) determines the amount of state change when it is greater than ).

[0071] In the example illustrated in FIG. 5, the battery state estimation device (120) through the battery model the surface concentration of each of the electrodes of the battery (110), the estimated voltage (V) of the battery (110) est The SOC of the battery (110) and the battery (hereinafter referred to as "SOC2" in FIG. 5) can be determined.

[0072] The battery state estimation device (120) is the sensing voltage (V) of the battery (110). sen Estimated voltage (V) of ) and battery (110) est The voltage difference (dV) between ) can be determined. For example, the estimated voltage (V est ) is the sensing voltage (V sen It can be 200mV greater than ). The battery state estimation device (120) is "sensing voltage (V sen )―Estimated voltage (V est According to ”, the voltage difference (dV) can be calculated as -200mV. A negative voltage difference (dV) (e.g., -200mV) may mean that the battery model has determined SOC2 to be greater than the actual SOC of the battery (110) due to the internal state of the battery model. The battery state estimation device (120) may perform corrections (e.g., surface concentration correction, correction of the internal state of the battery model, etc.) so that the SOC to be determined by the battery model afterwards can be close to the actual SOC of the battery (110) (or so that the battery model can determine a lower SOC afterwards).

[0073] In the example illustrated in FIG. 5, the surface concentration of the positive electrode of the battery (110) may be Y1, and the surface concentration of the negative electrode of the battery (110) may be X1.

[0074] The battery state estimation device (120) can obtain an OCP value (e.g., 3.95V) corresponding to the surface concentration (Y1) of the positive electrode from the first OCP table (or graph (410)). The battery state estimation device (120) can obtain an OCP value (e.g., 0.17V) corresponding to the surface concentration (X1) of the negative electrode from the second OCP table (or graph (420)).

[0075] The battery state estimation device (120) can calculate a difference value (e.g., 3.78V) between an OCP value (e.g., 3.95V) and an OCP value (e.g., 0.17V). The battery state estimation device (120) can determine the calculated difference value (e.g., 3.78V) as the OCV1 of the battery (110).

[0076] The battery state estimation device (120) can determine a correction value (or concentration shift amount) (dY) (511) for correcting the surface concentration (Y1) of the positive electrode based on the initial state change amount (d_SOC_0). In an embodiment, if the voltage difference (dV) is negative, the battery state estimation device (120) can change (or convert) the sign of the initial state change amount (d_SOC_0). For example, d_SOC_0 may be 3%. As described through FIG. 4, if the voltage difference (dV) is positive, the battery state estimation device (120) can use d_SOC_0 without changing (or converting) the sign. If the voltage difference (dV) is negative, the battery state estimation device (120) can change (or convert) d_SOC_0 to -3% through a sign change (or conversion). The battery state estimation device (120) can determine a correction value (or concentration shift amount) (dX) (521) to correct the surface concentration (X1) of the negative electrode through the changed initial state change amount (-d_SOC_0) (e.g., -3%).

[0077] For example, the battery state estimation device (120) can determine dY (511) (e.g., dY = -d_SOC_0 × d_SOC_CA) using a predetermined value (d_SOC_CA) and a changed initial state change amount (-d_SOC_0) for the positive electrode of the battery (110). Here, -d_SOC_0 can be negative and d_SOC_CA can be negative as described above, so dY (511) can be positive. The battery state estimation device (120) can determine dX (521) (e.g., dX = -d_SOC_0 × d_SOC_AN) using a predetermined value (d_SOC_AN) and a changed initial state change amount (-d_SOC_0) for the negative electrode of the battery (110). Here, -d_SOC_0 can be negative as described above, and d_SOC_AN can be positive as described above, so dX (521) can be negative. Since the voltage difference (dV) is negative, dY (511) can be in the direction of increasing the anode concentration (e.g., surface concentration or stoichiometric concentration of the anode), and dX (521) can be in the direction of decreasing the cathode concentration (e.g., surface concentration or stoichiometric concentration of the cathode).

[0078] The battery state estimation device (120) can correct the surface concentration (Y1) of the positive electrode through dY (511). The corrected surface concentration (Y1+dY) of the positive electrode may be greater than the surface concentration (Y1) of the positive electrode. The battery state estimation device (120) can obtain an OCP value (e.g., 3.91V) corresponding to the corrected surface concentration (Y1+dY) of the positive electrode from the first OCP table (or graph (410)). The battery state estimation device (120) can correct the surface concentration (X1) of the negative electrode through dX (521). dX (521) may be negative, so that the corrected surface concentration (X1+dX) of the negative electrode may be smaller than the surface concentration (X1) of the negative electrode. The battery state estimation device (120) can obtain an OCP value (e.g., 0.21V) corresponding to the corrected surface concentration (X1+dX) of the negative electrode in the second OCP table (or graph (420)).

[0079] The battery state estimation device (120) can calculate a difference value (e.g., 3.7V) between an OCP value (e.g., 3.91V) corresponding to the corrected surface concentration of the positive electrode and an OCP value (e.g., 0.21V) corresponding to the corrected surface concentration of the negative electrode. The battery state estimation device (120) can determine the calculated difference value (e.g., 3.7V) as the OCV3 of the battery (110).

[0080] The battery state estimation device (120) can determine the amount of change in state (or amount of state error) (d_SOC) of the battery (110) using the changed initial state change amount (-d_SOC_0) (e.g., -3%), the OCV1 of the battery (110) (e.g., 3.78V), the OCV3 of the battery (110) (e.g., 3.7V), and the voltage difference (dV) (e.g., -0.2V). For example, the battery state estimation device (120) can determine the amount of change in state (d_SOC) of the battery (110) through the above Equation 1. According to the above Equation 1, the ratio between d_SOC_0 and d_SOC may be the same as the ratio between the OCV difference (e.g., OCV3―OCV1 = 3.7V―3.78V = -0.08V) and the voltage difference (dV). If -d_SOC_0 is, for example, -3%, then d_SOC can be "-3% × (-0.2) / (-0.08) = -7.5%". In other words, in the example illustrated in FIG. 5, the battery state estimation device (120) can determine d_SOC to be -7.5%. As described above, the battery state estimation device (120) can update the battery model based on the amount of change in state (d_SOC) (e.g., -7.5%), and can determine the state information (e.g., SOC) of the battery (110) through the updated battery model. Accordingly, the battery state estimation device (120) can determine highly accurate state information.

[0082] FIG. 6 is a drawing illustrating another example of determining the amount of change in the state of a battery according to one embodiment.

[0083] Referring to FIG. 6, the battery state estimation device (120) can determine a first OCV of the battery (110) (e.g., OCV1 described through FIG. 4 and FIG. 5). The battery state estimation device (120) can determine an optimal value (610) of the state change amount (d_SOC) by performing an optimization operation to optimize the state change amount (d_SOC) based on the determined voltage difference (dV), the surface concentration of each of the electrodes of the battery (110), and the determined first OCV. In the example described through FIG. 6, the determined voltage difference (dV) may be positive.

[0084] For example, the battery state estimation device (120) can determine the optimal value (610) of the state change amount (d_SOC) by performing an optimization operation through the following mathematical formula 2.

[0085]

[0086]

[0087]

[0088]

[0089]

[0091] In the above mathematical formula 2, OCV(SOC) may represent the OCV at the SOC determined by the battery model (e.g., the above-described SOC1). OCV(SOC+d_SOC) may represent the OCV at SOC+d_SOC. Alternatively, OCV(SOC+d_SOC) may represent the OCV with d_SOC taken into account. OCP_CA() may represent the first OCP table (or graph (410)), and OCP_AN() may represent the second OCP table (or graph (420)). OCP_CA(Y) may represent the positive OCP corresponding to the surface concentration (Y) of the positive electrode of the battery (110), and OCP_AN(X) may represent the negative OCP corresponding to the surface concentration (X) of the negative electrode of the battery (110). The surface concentration of the positive electrode (Y) and the surface concentration of the negative electrode (X) can be determined by a battery model. d_SOC_0, d_SOC_CA, and d_SOC_AN, respectively, can represent the initial state change amount, a predetermined value for the positive electrode of the battery (110), and a predetermined value for the negative electrode of the battery (110), respectively, as described above.

[0092] For example, the battery state estimation device (120) can determine the surface concentrations of the positive and negative electrodes of the battery (110) as Y1 and X1, respectively, through a battery model, and can determine the SOC of the battery (110) as SOC1 through a battery model. The battery state estimation device (120) can determine the voltage difference (dV) as 300mV. The battery state estimation device (120) can determine OCP_CA (Y1) as 3.95V through a first OCP table and OCP_AN (X1) as 0.17V through a second OCP table. The battery state estimation device (120) can determine OCV (SOC1) as 3.78V.

[0093] Based on "dV=OCV(SOC+d_SOC)―OCV(SOC)" of the above mathematical formula 2, the battery state estimation device (120) can set the difference between OCV(SOC) and OCV(SOC+d_SOC) to be equal to the voltage difference (dV) (e.g., 0.3V). The initial state change amount (d_SOC_0) can be, for example, 0.03 (or 3%), d_SOC_CA can be, for example, -0.6, and d_SOC_AN can be, for example, 0.89. The battery state estimation device (120) can determine dY to be -0.018 and dX to be 0.0267.

[0094] The battery state estimation device (120) can determine the optimal value (610) of the state change amount (d_SOC) by performing an optimization operation on dV=OCV(SOC1+d_SOC)―OCV(SOC1) and OCV(SOC1+d_SOC)=OCP_CA(Y1+dY)-OCP_AN(X1+dX). The optimization operation may include, for example, a global optimization method, a gradient descent method, etc.

[0095] When the battery state estimation device (120) determines an optimal value (610), it can update the battery model based on the optimal value (610) and determine the state information (e.g., SOC) of the battery (110) through the updated battery model. At this time, the voltage difference (dV) described above can be minimized in the case of the determined state information. Accordingly, the battery state estimation device (120) can determine state information with high accuracy.

[0097] FIGS. 7a, FIGS. 7b, and FIGS. 8 are drawings illustrating other examples of determining the amount of state change of a battery according to one embodiment.

[0098] Referring to FIG. 7a, a graph (710) of positive OCP (OCP_CA) according to SOC and a graph (720) of negative OCP (OCP_AN) according to SOC are shown. The graph (710) of positive OCP according to SOC can be derived from, for example, the graph (740) of OCP according to the positive concentration (e.g., stoichiometric concentration of the positive) of the battery (110) shown in FIG. 7b. The graph (710) can be derived from the graph (740) by converting the positive concentration of the battery (110) into SOC according to a defined conversion relationship. The graph (720) of negative OCP according to SOC can be derived from, for example, the graph (750) of OCP according to the negative concentration (e.g., stoichiometric concentration of the negative) of the battery (110) shown in FIG. 7b. According to a predetermined conversion relationship, the negative concentration of the battery (110) is converted into SOC, thereby allowing the graph (720) to be derived from the graph (750).

[0099] According to one embodiment, the derivation of graph (710) from graph (740) and the derivation of graph (720) from graph (750) can be performed by a battery state estimation device (120). This is not limited thereto, and the battery state estimation device (120) may have graph (710) (or a table corresponding to graph (710)) and graph (720) (or a table corresponding to graph (720)) stored in advance.

[0100] The battery state estimation device (120) can determine the surface concentration of the positive electrode of the battery (110) to, for example, 0.42 and the surface concentration of the negative electrode of the battery (110) to, for example, 0.5 using a battery model, and can estimate the OCV and voltage of the battery (110).

[0101] The battery state estimation device (120) can determine the voltage difference (dV) between the sensing voltage of the battery (110) and the estimated voltage of the battery (120) as, for example, -0.15.

[0102] The battery state estimation device (120) can find the SOC (e.g., 0.75) corresponding to the surface concentration of the positive electrode (e.g., 0.42) through a predetermined conversion relationship. The battery state estimation device (120) can find the SOC (e.g., 0.5) corresponding to the surface concentration of the negative electrode (e.g., 0.5) through a predetermined conversion relationship.

[0103] The battery state estimation device (120) can move the graph (710) and / or the graph (720) so that the SOC (e.g., 0.75) corresponding to the surface concentration of the positive electrode (e.g., 0.42) and the SOC (e.g., 0.5) corresponding to the surface concentration of the negative electrode (e.g., 0.5) are aligned. Accordingly, as in the example shown in FIG. 7a, the SOC (e.g., 0.75) corresponding to the surface concentration of the positive electrode (e.g., 0.42) and the surface concentration of the negative electrode (e.g., 0.5) can be aligned with the line (701). For convenience, the graph (710) in the example shown in FIG. 7a is described as being moved.

[0104] The battery state estimation device (120) can obtain graph (730) by subtracting graph (720) from the shifted graph (710). The x-axis of graph (730) may represent relative SOC (e.g., the result of subtracting the SOC on the x-axis of graph (720) from the SOC on the x-axis of the shifted graph (710). SOC on the x-axis of graph (730). a 0.25, for example. The y-axis of the graph (730) may represent the difference between the positive OCP (OCP_CA) and the negative OCP (OCP_AN). The difference between the positive OCP (OCP_CA) and the negative OCP (OCP_AN) may represent, for example, OCV.

[0105] The battery state estimation device (120) estimates the OCV (e.g., the OCV of FIG. 7a) est A voltage difference (dV) (731) (e.g., -0.15) can be applied to ). The battery state estimation device (120) can see "OCV" in the graph (730). estSOC corresponding to + dV(731) b It can determine the battery state estimation device (120). The estimated OCV (OCV est SOC corresponding to ) a (e.g., 0.75-0.5=0.25) and SOC b The difference between them can be determined as the initial state change amount (d_SOC_0). In the example illustrated in FIG. 7a, the battery state estimation device (120) can determine the initial state change amount (d_SOC_0) as -13%.

[0106] A predetermined value (d_SOC_CA) for the positive electrode of the battery (110) may be, for example, -0.6, and a predetermined value (d_SOC_AN) for the negative electrode of the battery (110) may be, for example, 0.89.

[0107] The battery state estimation device (120) can determine dY (711) of FIG. 7a to be 0.078 according to “dY=d_SOC_0×d_SOC_CA” and determine dX (721) of FIG. 7a to be -0.1157 according to “dX=d_SOC_0×d_SOC_AN”.

[0108] The battery state estimation device (120) can determine a ratio value (hereinafter referred to as the "first ratio value") (e.g., -1.8) corresponding to the surface concentration (e.g., 0.42) of the positive electrode of the battery (110) using the graph (810) of FIG. 8. The graph (810) can represent, for example, the relationship between the ratio (dOCP / dY) between the change in positive electrode concentration (dY) of the battery (110) and the change in OCP of the positive electrode (dOCP), and the positive electrode concentration (e.g., stoichiometric concentration of the positive electrode). The graph (810) can be determined, for example, based on a first OCP table.

[0109] The battery state estimation device (120) can determine a ratio value (hereinafter referred to as the "second ratio value") (e.g., -0.4) corresponding to the surface concentration (e.g., 0.5) of the negative electrode of the battery (110) using the graph (820) of FIG. 8. The graph (820) can represent, for example, the relationship between the ratio (dOCP / dX) between the change in negative electrode concentration (dX) of the battery (110) and the change in OCP of the negative electrode (dOCP), and the negative electrode concentration (e.g., stoichiometric concentration of the negative electrode). The graph (820) can be determined, for example, based on a second OCP table.

[0110] The battery state estimation device (120) can determine the change in OCP value of the positive electrode (dOCP_CA) based on the first ratio value and dY (711), and can determine the change in OCP value of the negative electrode (dOCP_AN) based on the second ratio value and dX (721). dOCP can be determined by multiplying dY by dOCP / dY. The battery state estimation device (120) can determine the change in OCP value of the positive electrode (dOCP_CA) (e.g., -0.1404) by multiplying the first ratio value (e.g., -1.8) by dY (711) (e.g., 0.078). Similarly, the battery state estimation device (120) can determine the OCP change value (dOCP_AN) (e.g., 0.04628) of the negative electrode by multiplying the second ratio value (e.g., -0.4) by dX (721) (e.g., -0.1157).

[0111] The battery state estimation device (120) can determine the OCV difference (dOCV) of the battery (110) based on the change in OCP value of the positive electrode (dOCP_CA) and the change in OCP value of the negative electrode (dOCP_AN). For example, "dOCV = dOCP_CA + dOCP_AN". The battery state estimation device (120) can determine the OCV difference (dOCV) of the battery (110) (e.g., -0.09412) according to "dOCV = dOCP_CA + dOCP_AN".

[0112] The battery state estimation device (120) can determine the state change amount (d_SOC) using the initial state change amount (d_SOC_0) (e.g., -0.13 or -13%), the OCV difference (dOCV) (e.g., about -0.094), and the voltage difference (dV) (e.g., -0.15). For example, the battery state estimation device (120) can determine the state change amount (d_SOC) (e.g., -20.7%) according to the above-described mathematical formula 1.

[0113] According to an embodiment, the battery state estimation device (120) may use the larger ratio value when the size of either the first ratio value or the second ratio value is larger than the other by a certain level. For example, the battery state estimation device (120) may determine the first ratio value to be -1.8 and the second ratio value to be -0.4. In this case, the battery state estimation device (120) may determine that the size of the first ratio value (e.g., 1.8) is larger than the size of the second ratio value (e.g., 0.4) by a certain level. The battery state estimation device (120) may not use the second ratio value and may use the first ratio value. The battery state estimation device (120) may determine dY (711) of FIG. 7a to be 0.078 according to "dY=d_SOC_0×d_SOC_CA". The battery state estimation device (120) can determine the change in OCP value of the positive electrode (dOCP_CA) (e.g., -0.1404) by multiplying the first ratio value (e.g., -1.8) by dY (711) (e.g., 0.078). The battery state estimation device (120) can determine the change in OCP value of the positive electrode (dOCP_CA) as the OCV difference (dOCV). If the magnitude of the first ratio value is greater than the magnitude of the second ratio value by a certain level, dOCV = dOCP_CA = -0.1404. The battery state estimation device (120) can determine the change in state (d_SOC) as -13.9% according to the above mathematical formula 1.

[0115] FIG. 9 is a diagram illustrating an example of determining the initial state change amount of a battery state estimation device according to one embodiment.

[0116] A graph (910) between SOC and OCV is shown in Fig. 9.

[0117] When the battery state estimation device (120) determines the voltage difference (dV), it can determine the initial state change amount (d_SOC_0) using the determined voltage difference (dV) and the graph (910) (or the table between SOC and OCV).

[0118] For example, the battery state estimation device (120) estimates the battery's voltage (V) through a battery model. est The battery state estimation device (120) can determine the SOC (hereinafter referred to as "SOC1" in FIG. 9) of the battery (110). sen Estimated voltage (V) of ) and battery (110) est The voltage difference (dV) between them can be determined. The battery state estimation device (120) can obtain OCV1 corresponding to SOC1 from the graph (910). The battery state estimation device (120) can obtain SOC2 corresponding to the sum result (OCV1+dV) (OCV2 in FIG. 9) of the obtained OCV1 and the determined voltage difference (dV). The battery state estimation device (120) can determine the difference between SOC1 and SOC2 as the initial state change amount (d_SOC_0).

[0120] FIG. 10 is a block diagram illustrating the configuration of a battery state estimation device according to one embodiment.

[0121] Referring to FIG. 10, a battery state estimation device (120) according to one embodiment may include a processor (1010), a voltage sensor (1020), and a memory (1030).

[0122] The memory (1030) can store one or more instructions that can be executed by the processor (1010).

[0123] The memory (1030) can store a battery model (e.g., an electrochemical model).

[0124] The processor (1010) can determine the estimated voltage of the battery (110) and the surface concentration of each of the electrodes of the battery (110) through the battery model.

[0125] The processor (1010) can obtain the sensing voltage of the battery (110) using the voltage sensor (1020).

[0126] The processor (1010) can determine the voltage difference (dV) between the acquired sensing voltage and the determined estimated voltage.

[0127] The processor (1010) can determine the amount of change in state of the battery (d_SOC) based on the determined voltage difference and the determined surface concentration.

[0128] According to one embodiment, the processor (1010) can determine the first OCP of each electrode of the battery (110) using each determined surface concentration. For example, the processor (1010) can determine the first OCP of each electrode of the battery (110) using each OCP table representing the relationship between the stoichiometric concentration of each electrode of the battery (110) and the OCP, and each determined surface concentration.

[0129] The processor (1010) can determine the first OCV of the battery (110) (e.g., the OCV1 described above) using each determined first OCP. The processor (1010) can correct each surface concentration based on the initial state change amount (d_SOC_0). For example, the processor (1010) can determine each correction value for correcting each surface concentration using a predetermined value and the initial state change amount (d_SOC_0) for each electrode of the battery (110), and can correct each surface concentration based on each determined correction value.

[0130] The processor (1010) can determine the second OCP of each electrode of the battery (110) using each corrected surface concentration. For example, the processor (1010) can determine the second OCP of each electrode of the battery (110) using each OCP table and each corrected surface concentration. The processor (1010) can determine the second OCV of the battery (110) (e.g., the aforementioned OCV2 or the aforementioned OCV3) using each determined second OCP.

[0131] The processor (1010) can determine a state change amount (d_SOC) using a determined first OCV, a determined second OCV, an initial state change amount, and a determined voltage difference. For example, the processor (1010) can determine a difference value between the determined second OCV and the determined first OCV, and can determine a state change amount by applying the ratio between the determined difference value and the determined voltage difference (dV) to the initial state change amount.

[0132] According to one embodiment, the processor (1010) can determine the optimal value of the state change amount by performing an optimization operation to optimize the state change amount (d_SOC) based on a determined voltage difference (dV), a determined surface concentration, and a determined OCV (e.g., a first OCV). At this time, the processor (1010) can perform the optimization operation by setting the voltage difference between the OCV (e.g., OCV(SOC+d_SOC)) that takes the state change amount into account and the determined OCV to be equal to the determined voltage difference (dV).

[0133] According to one embodiment, the processor (1010) may obtain a first ratio value corresponding to the surface concentration of the first electrode from a first table (or graph (810)) representing the relationship between the ratio between the change in concentration of the first electrode (e.g., positive electrode) of the battery (110) and the change in OCP and the concentration of the first electrode. The first table may be determined, for example, from the graph (810). The processor (1010) may obtain a second ratio value corresponding to the surface concentration of the second electrode from a second table (or graph (820)) representing the relationship between the ratio between the change in concentration of the second electrode (e.g., negative electrode) of the battery (110) and the change in OCP and the concentration of the second electrode. The second table may be determined, for example, from the graph (820).

[0134] The processor (1010) can determine a state change amount using a determined voltage difference (dV), a obtained first ratio value, a obtained second ratio value, and an initial state change amount. For example, the processor (1010) can determine a first correction value (e.g., dY (711) in FIG. 7a) for correcting the surface concentration of the first electrode by applying the initial state change amount (e.g., initial state change amount (732) in FIG. 7a) to a predetermined value (e.g., d_SOC_CA) for the first electrode. The processor (1010) can determine a first OCP change amount value of the first electrode (e.g., the above-described dOCP_CA) using the determined first correction value and the obtained first ratio value. The processor (1010) can determine a second correction value (e.g., dX (721) in FIG. 7a) for correcting the surface concentration of the second electrode by applying an initial state change amount (e.g., initial state change amount (732) in FIG. 7a) to a predetermined value (e.g., d_SOC_AN) for the second electrode. The processor (1010) can determine a second OCP change amount value of the second electrode (e.g., the aforementioned dOCP_AN) using the determined second correction value and the acquired second ratio value. The processor (1010) can calculate the sum of the determined first OCP change amount value and the determined second OCP change amount value. At this time, the calculated sum may correspond to the aforementioned dOCV. The processor (1010) can determine the state change amount (d_SOC) by applying the ratio between the determined voltage difference and the calculated sum (e.g., dV / dOCV) to the initial state change amount (e.g., the initial state change amount (732) in FIG. 7a). Since an example of determining the state change amount using the determined voltage difference (dV), the obtained first ratio value, the obtained second ratio value, and the initial state change amount has been explained through FIG. 7a, FIG. 7b, and FIG. 8, a detailed description is omitted.

[0135] The processor (1010) can update the battery model based on a determined amount of state change. For example, the processor (1010) can update the battery model by correcting at least one of the parameters of the electrochemical model (e.g., ion concentration distribution within active material particles and / or ion concentration distribution within electrodes) based on a determined amount of state change.

[0136] The processor (1010) can determine the state information (e.g., SOC, etc.) of the battery (110) based on the updated battery model.

[0137] The embodiments described through FIGS. 1 to 9 can be applied to the battery state estimation device (120) of FIG. 10.

[0139] FIG. 11 is a block diagram illustrating an electronic device including a battery state estimation device according to one embodiment.

[0140] Referring to FIG. 11, an electronic device (1100) according to one embodiment includes a battery (110) and a battery state estimation device (120).

[0141] An electronic device (1100) according to one embodiment can be applied to a vehicle (e.g., electric vehicle, etc.), a mobile device (e.g., smartphone, tablet PC, etc.).

[0142] The electronic device (1100) can determine the estimated voltage of the battery (110) and the surface concentration of each of the electrodes of the battery (110) through a battery model. The electronic device (1100) can obtain the sensing voltage of the battery (110) using a voltage sensor. The electronic device (1100) can determine the voltage difference between the obtained sensing voltage and the determined estimated voltage. The electronic device (1100) can determine the amount of state change of the battery (110) based on the determined voltage difference and the determined surface concentrations. The electronic device (1100) can update the battery model based on the determined amount of state change. The electronic device (1100) can determine the state information of the battery (110) based on the updated battery model. The electronic device (1100) can display the determined state information on a display.

[0143] The embodiments described through FIGS. 1 to 10 can be applied to the electronic device (1100) of FIG. 11.

[0145] FIG. 12 is a block diagram illustrating a mobile device according to one embodiment.

[0146] Referring to FIG. 12, a mobile device (1200) according to one embodiment may include a processor (1210), memory (1220), battery (1230), a Power Management Integrated Circuit (PMIC) (1240), and a display (1250).

[0147] The memory (1220) may contain one or more instructions executable by the processor (1210). The memory (1220) may store a battery model.

[0148] The PMIC (1240) can charge the battery (1230) with power received from outside the mobile device (1200) (e.g., a travel adapter or a wireless charger). The PMIC (1240) can supply power stored in the battery (1230) to a component of the mobile device (1200) (e.g., a processor (1210), etc.).

[0149] The PMIC (1240) can sense the voltage of the battery (1230) through a voltage sensor to obtain a sensed voltage and can transmit the obtained sensed voltage to the processor (1210). As another example, although not shown in FIG. 12, a voltage sensor may be located near the battery (1230), and the voltage sensor may sense the voltage of the battery (1230) and transmit the obtained sensed voltage to the processor (1210).

[0150] The processor (1210) can perform at least some or all of the operations of the battery state estimation device (120) described above. The processor (1210) can determine the estimated voltage of the battery (1230) and the surface concentration of each of the electrodes of the battery (1230) through the battery model. The processor (1210) can determine the voltage difference between the acquired sensing voltage and the determined estimated voltage. The processor (1210) can determine the amount of state change of the battery (1230) based on the determined voltage difference and the determined surface concentration. The processor (1210) can update the battery model based on the determined amount of state change. The processor (1210) can determine the state information of the battery (1230) based on the updated battery model. The processor (1210) can control the display (1250) so that the determined state information is displayed on the display (1250).

[0151] The embodiments described through FIGS. 1 to 11 can be applied to the mobile device (1200) of FIG. 12.

[0153] The embodiments described above may be implemented as hardware components, software components, and / or combinations of hardware and software components. For example, the devices, methods, and components described in the embodiments may be implemented using a general-purpose computer or a special-purpose computer, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. In addition, other processing configurations, such as parallel processors, are also possible.

[0154] 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 in order 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 computer-readable recording media.

[0155] 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 store program instructions, data files, data structures, etc., either individually or in combination, and the program instructions recorded on the medium may be those specifically designed and configured for the embodiment or 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.

[0156] The hardware device described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

[0157] Although the embodiments have been described above with reference to the limited drawings, those skilled in the art can apply various technical modifications and variations based thereon. For example, suitable results may be achieved even if the described techniques are performed in a different order than described, and / or if 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.

[0158] 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 method for estimating the state of a battery of an electronic device comprises: a step of determining an estimated voltage of the battery and a surface concentration of each electrode of the battery through a battery model; a step of obtaining a sensing voltage of the battery using a voltage sensor; a step of determining a voltage difference between the obtained sensing voltage and the determined estimated voltage; a step of determining a state variation of the battery based on the determined voltage difference and each determined surface concentration; a step of updating the battery model based on the determined state variation; and a step of determining state information of the battery based on the updated battery model, wherein the step of determining the state variation comprises: a step of determining a first Open Circuit Voltage (OCV) of the battery based on each determined surface concentration; a step of correcting each determined surface concentration based on an initial state variation; and a step of determining a second OCV of the battery based on each corrected surface concentration. A battery state estimation method comprising the step of determining the state change amount using the first OCV, the second OCV, the initial state change amount, and the determined voltage difference, wherein the second OCV corresponds to the first OCV corrected based on the initial state change amount. Claim 2 A battery state estimation method according to claim 1, wherein the step of determining the first OCV comprises: determining a first open circuit potential (OCP) of each of the electrodes using each of the determined surface concentrations; and determining the first OCV using each of the determined first OCPs, and the step of determining the second OCV comprises: determining a second OCP of each of the electrodes using each of the corrected surface concentrations; and determining the second OCV using each of the determined second OCPs. Claim 3 A battery state estimation method according to claim 2, wherein the step of determining a first OCP of each of the electrodes comprises determining the first OCP of each of the electrodes using each OCP table representing the relationship between the stoichiometric concentration and OCP of each of the electrodes and each determined surface concentration. Claim 4 A battery state estimation method according to claim 2, wherein the step of determining the state change amount using the first OCV, the second OCV, the initial state change amount, and the determined voltage difference comprises: the step of determining the difference value between the determined second OCV and the determined first OCV; and the step of determining the state change amount by applying the ratio between the determined difference value and the determined voltage difference to the initial state change amount. Claim 5 A battery state estimation method according to claim 2, wherein the step of correcting each determined surface concentration comprises: a step of determining each correction value for correcting each determined surface concentration using a predetermined value for each of the electrodes and the initial state change amount; and a step of correcting each determined surface concentration based on each determined correction value. Claim 6 A battery state estimation method according to claim 1, wherein the step of determining the amount of state change comprises: a step of determining the OCP of each of the electrodes using the determined surface concentration; a step of determining the first OCV using the determined OCP; and a step of determining the optimal value of the amount of state change by performing an optimization operation to optimize the amount of state change based on the determined voltage difference, the determined surface concentration, and the first OCV. Claim 7 A battery state estimation method according to claim 6, wherein the step of determining the optimal value includes the step of performing the optimization operation by setting the voltage difference between the OCV considering the state change amount and the first OCV to be the same as the determined voltage difference. Claim 8 A battery state estimation method according to claim 1, wherein the step of determining the state change amount comprises: obtaining a first ratio value corresponding to the determined surface concentration of the first electrode from a first table representing the relationship between the ratio between the concentration change amount of the first electrode among the electrodes and the OCP change amount and the concentration of the first electrode; obtaining a second ratio value corresponding to the determined surface concentration of the second electrode from a second table representing the relationship between the ratio between the concentration change amount of the second electrode among the electrodes and the OCP change amount and the concentration of the second electrode; and determining the state change amount using the determined voltage difference, the obtained first ratio value, the obtained second ratio value, and the initial state change amount. Claim 9 A battery state estimation method according to claim 8, wherein the step of determining the state change amount using the determined voltage difference, the obtained first ratio value, the obtained second ratio value, and the initial state change amount comprises: a step of determining a first correction value for correcting the surface concentration of the first electrode by applying the initial state change amount to a predetermined value for the first electrode; a step of determining a first OCP change amount value of the first electrode using the determined first correction value and the obtained first ratio value; a step of determining a second correction value for correcting the surface concentration of the second electrode by applying the initial state change amount to a predetermined value for the second electrode; a step of determining a second OCP change amount value of the second electrode using the determined second correction value and the obtained second ratio value; a step of calculating the sum of the determined first OCP change amount value and the determined second OCP change amount value; and a step of determining the state change amount by applying the ratio between the determined voltage difference and the calculated sum to the initial state change amount. Claim 10 A battery state estimation method according to claim 1, wherein the step of updating the battery model includes the step of updating the internal state of the battery model by correcting at least one of the parameters of the battery model based on the determined amount of change in state. Claim 11 A computer-readable storage medium, wherein the computer-readable storage medium stores a program for executing a battery state estimation method, and the battery state estimation method comprises: a step of determining an estimated voltage of a battery and a surface concentration of each electrode of the battery through a battery model; a step of obtaining a sensing voltage of the battery using a voltage sensor; a step of determining a voltage difference between the obtained sensing voltage and the determined estimated voltage; a step of determining a state variation of the battery based on the determined voltage difference and each determined surface concentration; a step of updating the battery model based on the determined state variation; and a step of determining state information of the battery based on the updated battery model, wherein the step of determining the state variation comprises: a step of determining a first Open Circuit Voltage (OCV) of the battery based on each determined surface concentration; a step of correcting each determined surface concentration based on an initial state variation; and a step of determining a second OCV of the battery based on each corrected surface concentration. A computer-readable storage medium comprising the step of determining a state change amount using the first OCV, the second OCV, the initial state change amount, and the determined voltage difference, wherein the second OCV corresponds to the first OCV corrected based on the initial state change amount. Claim 12 As an electronic device, a battery; a voltage sensor; a memory for storing a battery model; and includes a processor operatively connected to the memory, wherein the processor determines the estimated voltage of the battery and the surface concentration of each electrode of the battery through the battery model, obtains the sensing voltage of the battery using the voltage sensor, determines the voltage difference between the obtained sensing voltage and the determined estimated voltage, determines the state variation of the battery based on the determined voltage difference and each determined surface concentration, updates the battery model based on the determined state variation, and determines state information of the battery based on the updated battery model, wherein the processor determines the first Open Circuit Voltage (OCV) of the battery based on each determined surface concentration, corrects each determined surface concentration based on the initial state variation, determines the second OCV of the battery based on each corrected surface concentration, determines the state variation using the first OCV, the second OCV, the initial state variation, and the determined voltage difference, and the second OCV is based on the first An electronic device corresponding to one with corrected OCV. Claim 13 An electronic device according to claim 12, wherein the processor determines a first open circuit potential (OCP) of each of the electrodes using each of the determined surface concentrations, determines a first OCV using each of the determined first OCPs, corrects each of the determined surface concentrations based on the initial state change amount, determines a second OCP of each of the electrodes using each of the corrected surface concentrations, and determines a second OCV using each of the determined second OCPs. Claim 14 In paragraph 13, the processor is an electronic device that determines a first OCP of each of the electrodes using each OCP table representing the relationship between the stoichiometric concentration of each of the electrodes and the OCP, and each determined surface concentration. Claim 15 An electronic device according to claim 13, wherein the processor determines a difference value between the second OCV and the first OCV, and determines a state change amount by applying the ratio between the determined difference value and the determined voltage difference to the initial state change amount. Claim 16 An electronic device according to claim 13, wherein the processor determines each correction value for correcting each determined surface concentration using a predetermined value for each of the electrodes and the initial state change amount, and corrects each determined surface concentration based on each determined correction value. Claim 17 An electronic device according to claim 12, wherein the processor determines the OCP of each of the electrodes using the determined surface concentration, determines the first OCV using the determined OCP, and determines the optimal value of the state change amount by performing an optimization operation to optimize the state change amount based on the determined voltage difference, the determined surface concentration, and the first OCV. Claim 18 An electronic device according to claim 17, wherein the processor performs the optimization operation by setting the voltage difference between the OCV considering the state change amount and the first OCV to be the same as the determined voltage difference. Claim 19 An electronic device according to claim 12, wherein the processor obtains a first ratio value corresponding to the determined surface concentration of the first electrode from a first table representing the relationship between the ratio between the concentration change amount of the first electrode among the electrodes and the OCP change amount and the concentration of the first electrode, obtains a second ratio value corresponding to the determined surface concentration of the second electrode from a second table representing the relationship between the ratio between the concentration change amount of the second electrode among the electrodes and the OCP change amount and the concentration of the second electrode, and determines the state change amount using the determined voltage difference, the obtained first ratio value, the obtained second ratio value, and the initial state change amount. Claim 20 In paragraph 12, the processor is an electronic device that controls the display so that the determined state information is displayed on the display of the electronic device.

Images