Method and apparatus for battery state estimation

Abstract

Methods and apparatus for battery state estimation are disclosed. A processor-implemented method includes determining a voltage difference between an estimated voltage of a battery determined by a battery model and a sensed voltage of the battery, determining a state of charge (SOC) error amount based on the determined voltage difference, determining a first cumulative SOC compensation amount, the first cumulative SOC compensation amount is a cumulative SOC compensation amount for compensating the SOC of the battery at a partial discharge time point of the battery, estimating a second cumulative SOC compensation amount at a complete discharge time point of the battery based on the determined first cumulative SOC compensation amount and a predetermined SOC compensation amount prediction graph, and adjusting the estimated second cumulative SOC compensation amount based on the determined SOC error amount, and updating an aging parameter of the battery model based on the adjusted second accumulated SOC compensation amount.

Description

[0001] This application claims the benefit of Korean Patent Application No. 10-2024-0015079, filed on Jan. 31, 2024, with the Korean Intellectual Property Office, the entire disclosure of which is incorporated herein by reference for all purposes. Technical Field

[0002] The following description relates to a method and apparatus for estimating a battery state. Background Art

[0003] There are various ways to estimate the state of a battery. For example, the state of a battery can generally be estimated by integrating the current of the battery or by using a battery model (e.g., a circuit model or an electrochemical model). Summary of the Invention

[0004] This Summary of the Invention is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary of the Invention is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to help determine the scope of the claimed subject matter.

[0005] In one general aspect, there is provided a processor-implemented method, the method including: determining a voltage difference between an estimated voltage of a battery determined by a battery model and a sensed voltage of the battery; determining a state of charge (SOC) error amount based on the determined voltage difference; determining a first cumulative SOC compensation amount, the first cumulative SOC compensation amount being a cumulative SOC compensation amount for compensating the SOC of the battery at a partial discharge time point of the battery; estimating a second cumulative SOC compensation amount at a full discharge time point of the battery based on the determined first cumulative SOC compensation amount and a predetermined SOC compensation amount prediction curve; adjusting the estimated second cumulative SOC compensation amount based on the determined SOC error amount; and updating an aging parameter of the battery model based on the adjusted second cumulative SOC compensation amount.

[0006] The step of adjusting the estimated second cumulative SOC compensation amount may include: adjusting the estimated second cumulative SOC compensation amount by subtracting the determined SOC error amount from the estimated second cumulative SOC compensation amount or adding the determined SOC error amount to the estimated second cumulative SOC compensation amount.

[0007] The step of determining the voltage difference may include: determining whether a start condition for determining the SOC error amount is satisfied; and in response to determining that the start condition is satisfied, determining the voltage difference.

[0008] The step of determining whether the start condition is satisfied may include: determining that the start condition is satisfied in response to an anode concentration of the battery reaching a predetermined concentration value or an SOC of the battery reaching a predetermined SOC value.

[0009] The step of estimating the second cumulative SOC compensation amount may include: obtaining a third cumulative SOC compensation amount corresponding to the partial discharge battery state at the partial discharge time point in the SOC compensation amount prediction curve graph; obtaining a fourth cumulative SOC compensation amount corresponding to the fully discharged battery state at the full discharge time point in the SOC compensation amount prediction curve graph; and using the determined first cumulative SOC compensation amount, the obtained third cumulative SOC compensation amount, and the obtained fourth cumulative SOC compensation amount to estimate the second cumulative SOC compensation amount.

[0010] The step of determining the SOC error amount may include: obtaining the OCV corresponding to the SOC of the battery determined by the battery model in the open circuit voltage (OCV) table; and determining the SOC error amount by reflecting the determined voltage difference in the obtained OCV.

[0011] The step of determining the SOC error amount may include: using the surface concentration of each of the plurality of electrodes of the battery to determine a first open circuit potential (OCP) of each of the plurality of electrodes; using each determined first OCP to determine a first OCV of the battery; compensating each determined surface concentration based on an initial SOC error amount; using each compensated surface concentration to determine a second OCP of each of the plurality of electrodes; using each determined second OCP to determine a second OCV of the battery; and using the determined first OCV, the determined second OCV, the initial SOC error amount, and the determined voltage difference to determine the SOC error amount.

[0012] The step of updating the aging parameter may include: storing an aging parameter value calculated based on the adjusted second cumulative SOC compensation amount in a memory; and in response to satisfying an update condition of the aging parameter, updating the aging parameter using one or more aging parameter values stored in the memory.

[0013] The step of updating the aging parameter may include: storing the adjusted second cumulative SOC compensation amount in a memory; in response to satisfying an update condition of the aging parameter, calculating an average value of the plurality of adjusted second cumulative SOC compensation amounts stored in the memory; and using the calculated average value to update the aging parameter.

[0014] The aging parameter may be an electrode balance offset.

[0015] In one general aspect, there is provided a processor-implemented method, the method comprising: determining an amount of state of charge (SOC) error based on a determined voltage difference between an estimated voltage of a battery determined by a battery model and a sensed voltage of the battery; estimating a second cumulative SOC compensation amount at a full discharge time point of the battery based on a first cumulative SOC compensation amount and a predetermined SOC compensation amount prediction curve, the first cumulative SOC compensation amount being a cumulative SOC compensation amount for compensating the SOC of the battery at a partial discharge time point of the battery; and updating an aging parameter of the battery model according to the estimated second cumulative SOC compensation amount adjusted based on the determined SOC error amount.

[0016] In one general aspect, there is provided an electronic device, the electronic device comprising: a processor configured to execute instructions; and a memory storing the instructions and a battery model, execution of the instructions configuring the processor to: determine a voltage difference between an estimated voltage of a battery determined by the battery model and a sensed voltage of the battery; determine an amount of state of charge (SOC) error based on the determined voltage difference; determine a first cumulative SOC compensation amount, the first cumulative SOC compensation amount being a cumulative SOC compensation amount for compensating the SOC of the battery at a partial discharge time point of the battery; estimate a second cumulative SOC compensation amount at a full discharge time point of the battery based on the determined first cumulative SOC compensation amount and a predetermined SOC compensation amount prediction curve; adjust the estimated second cumulative SOC compensation amount based on the determined SOC error amount; and update an aging parameter of the battery model based on the adjusted second cumulative SOC compensation amount.

[0017] The processor may further be configured to adjust the estimated second cumulative SOC compensation amount by subtracting the determined SOC error amount from the estimated second cumulative SOC compensation amount or adding the estimated second cumulative SOC compensation amount to the determined SOC error amount.

[0018] The processor may further be configured to: determine whether a start condition for determining the SOC error amount is satisfied; and in response to determining that the start condition is satisfied, determine the voltage difference.

[0019] The processor may further be configured to: in response to an anode concentration of the battery reaching a predetermined concentration value or an SOC of the battery reaching a predetermined SOC value, determine that the start condition is satisfied.

[0020] The processor may also be configured to: obtain a third cumulative SOC compensation amount corresponding to the partial discharge battery state at the partial discharge time point in the SOC compensation amount prediction curve graph; obtain a fourth cumulative SOC compensation amount corresponding to the fully discharged battery state at the full discharge time point in the SOC compensation amount prediction curve graph; and estimate the second cumulative SOC compensation amount using the determined first cumulative SOC compensation amount, the obtained third cumulative SOC compensation amount, and the obtained fourth cumulative SOC compensation amount.

[0021] The processor may also be configured to: obtain an OCV corresponding to the SOC of the battery determined by the battery model in an open circuit voltage (OCV) table; and determine the SOC error amount by reflecting the determined voltage difference in the obtained OCV.

[0022] The processor may also be configured to: determine a first open circuit potential (OCP) of each of the plurality of electrodes of the battery using the surface concentration of each of the plurality of electrodes of the battery; determine a first OCV of the battery using each determined first OCP; compensate each determined surface concentration based on an initial SOC error amount; determine a second OCP of each of the plurality of electrodes using each compensated surface concentration; determine a second OCV of the battery using each determined second OCP; and determine the SOC error amount using the determined first OCV, the determined second OCV, the initial SOC error amount, and the determined voltage difference.

[0023] The processor may also be configured to: store an aging parameter value calculated based on the adjusted second cumulative SOC compensation amount in a memory; and update the aging parameter using one or more aging parameter values stored in the memory in response to satisfying an update condition of the aging parameter.

[0024] The processor may also be configured to: store the adjusted second cumulative SOC compensation amount in a memory; calculate an average value of the plurality of adjusted second cumulative SOC compensation amounts stored in the memory in response to satisfying an update condition of the aging parameter; and update the aging parameter using the calculated average value.

[0025] Other features and aspects will be apparent from the following detailed description, the drawings, and the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 Shows an example battery system according to one or more embodiments.

[0027] Figure 2 Shows an example electrochemical model according to one or more embodiments.

[0028] Figure 3Shows an example process of an operation compensator according to one or more embodiments.

[0029] Figure 4 Shows an example compensator according to one or more embodiments.

[0030] Figure 5 Shows an example process of an operation compensator according to one or more embodiments.

[0031] Figure 6 Shows an example process of determining a state of charge (SOC) compensation amount prediction curve according to one or more embodiments.

[0032] Figure 7 Shows an example process of estimating an accumulated SOC compensation amount according to one or more embodiments.

[0033] Figure 8 and Figure 9 Shows an example process of determining an SOC compensation amount prediction curve according to one or more embodiments.

[0034] Figure 10 Shows an example of a voltage difference according to one or more embodiments.

[0035] Figure 11 Shows an example method of estimating a battery state according to one or more embodiments.

[0036] Figure 12 and Figure 13 Shows an example process of determining an SOC error amount by a battery state estimation device according to one or more embodiments.

[0037] Figure 14 and Figure 15 Shows an example process of determining an SOC error amount by a battery state estimation device according to one or more embodiments.

[0038] Figure 16 Shows an example method of updating an aging parameter according to one or more embodiments.

[0039] Figure 17 Shows an example of an electronic device according to one or more embodiments.

[0040] Figure 18 Shows an example electronic device including a battery state estimation device according to one or more embodiments.

[0041] Figure 19 Shows an example mobile device according to one or more embodiments.

[0042] Throughout the drawings and the detailed description, unless otherwise described or provided, the same reference numerals can be understood to represent the same or similar elements, features, and structures. The drawings may not be drawn to scale, and for clarity, illustration, and convenience, the relative sizes, proportions, and depictions of elements in the drawings may be exaggerated. Detailed Description

[0043] The following detailed description is provided to assist the reader in obtaining a comprehensive understanding of the methods, apparatuses, and / or systems described herein. However, various changes, modifications, and equivalents of the methods, apparatuses, and / or systems described herein will be apparent after understanding the disclosure of this application. For example, the order within the operations described herein and / or the order of the operations described herein are merely examples and are not limited to those set forth herein, but rather may be changed as will be apparent after understanding the disclosure of this application, except for the order within the operations that must occur in a specific order and / or the order of the operations that must occur in a specific order. As another example, the order of the operations and / or the order within the operations may be performed in parallel, except for at least part of the order of the operations that must occur in a sequence (e.g., a specific order) and / or the order within the operations that must occur in a sequence (e.g., a specific order). Additionally, descriptions of features known after understanding the disclosure of this application may be omitted for greater clarity and conciseness.

[0044] The features described herein may be implemented in different forms and should not be construed as limited to the examples described herein. Instead, the examples described herein are provided only to illustrate some of the many possible ways of implementing the methods, apparatuses, and / or systems described herein that will be apparent after understanding the disclosure of this application.

[0045] Throughout the specification, when a component or element is described as "on", "connected to", "coupled to", or "joined to" another component, element, or layer, the component or element may be directly "on" the other component, element, or layer (e.g., in contact with the other component or element), directly "connected to", "coupled to", or "joined to" the other component, element, or layer, or one or more other components, elements, layers may reasonably exist therebetween. When a component or element is described as "directly on", "directly connected to", "directly coupled to", or "directly joined to" another component or element, no other elements may exist therebetween. Similarly, expressions such as "between" and "immediately between" and "adjacent to" and "immediately adjacent to" may be interpreted as described above.

[0046] The terms used herein are for describing various examples only and are not intended to limit the disclosure. Unless the context clearly indicates otherwise, the singular forms are also intended to include the plural forms. As a non-limiting example, the terms "comprising", "including", and "having" indicate the presence of stated features, quantities, operations, components, elements, and / or combinations thereof, but do not preclude the presence or addition of one or more other features, quantities, operations, components, elements, and / or combinations thereof, or optionally the presence of optionally stated features, quantities, operations, components, elements, and / or combinations thereof. Further, while one embodiment may state such terms as "comprising", "including", and "having" to indicate the presence of stated features, quantities, operations, components, elements, and / or combinations thereof, there may be other embodiments that do not have one or more of the stated features, quantities, operations, components, elements, and / or combinations thereof.

[0047] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains and as commonly understood based on the disclosure of this application. Unless explicitly defined as such herein, terms (such as those defined in a general dictionary) should be interpreted as having a meaning consistent with their meaning in the context of the relevant field and the disclosure of this application, and should not be interpreted in an idealized or overly formal sense. The use of the term "may" herein with respect to an example or embodiment (e.g., with respect to what an example or embodiment may include or implement) means that there is at least one example or embodiment that includes or implements such a feature, and all examples are not limited thereto.

[0048] It may generally be difficult to estimate some aging parameters in an actual battery usage environment, where the user of the device may have a unique operation mode that may affect the aging of the battery. For example, as an aging parameter, an electrode balance shift may be estimated at a low state of charge (SOC) or at the anode stoichiometric concentration at the full discharge time point, and the corresponding estimation conditions may not be easily achieved according to the user's actual battery usage pattern. Therefore, there is a desire to accurately estimate the electrode balance shift at a partial discharge time point, which is before reaching the full discharge time point.

[0049] Figure 1 An example battery system according to one or more embodiments is shown.

[0050] Referring to Figure 1 , in one non-limiting example, the battery system 100 may include a battery 110 and a battery state estimation device 120.

[0051] The battery 110 may be one or more battery cells, a battery module, or a battery pack, and may be a rechargeable battery.

[0052] In one example, the battery state estimation device 120 may be a device for estimating the state of the battery for optimal management of the battery 110, and in one example, the battery state estimation device 120 may include a battery management system (BMS). The battery state estimation device 120 may use one or more sensors (e.g., at least one of a voltage sensor, a current sensor, and a temperature sensor) to sense the battery 110. In other words, the battery state estimation device 120 collects the sensed data obtained by sensing the battery 110. In one example, the sensed data may include any one or any combination of voltage data, current data, and temperature data. In one example, the battery state estimation device 120 may measure the measurement data of the battery, and the measurement data of the battery includes any one or more of the measured voltage data, current data, and temperature data. However, the sensing or measurement of the battery is not limited thereto.

[0053] The battery state estimation device 120 may estimate (i.e., calculate or determine) the state information of the battery 110 based on the sensed data and output the estimated state information. The state information may include, for example, any one or any combination of state of charge (SOC), relative state of charge (RSOC), state of health (SOH), and abnormal state information. The battery model for estimating the state information may be an electrochemical model. The electrochemical model will be described in more detail below with reference to Figure 2 More detailed description of the electrochemical model.

[0054] Since the available area of the battery 110 may be expanded according to the accuracy of estimating the state information of the battery 110, estimating the accurate state information of the battery 110 may be related to the operation of the battery state estimation device 120. The battery state estimation device 120 may reflect the accurate aging state of the battery 110 in the battery model, so as to estimate the state information reflecting the aging state of the battery 110 with high accuracy.

[0055] There are various aging factors of the battery 110 (such as an increase in a simple resistance component, a decrease in the amount of a cathode active material or an anode active material, and the occurrence of lithium (Li) plating). The aspects of aging may vary according to the usage pattern and usage environment of a user who uses the battery. Specifically, the aging characteristics of the battery 110 may vary according to the usage form and environment of the user who uses the battery. In one example, even when the battery 110 has the same capacity reduction due to aging, the internal state of the aged battery 110 may be different. To accurately reflect aging in the battery model, the aging parameter of the battery 110 estimated by analyzing the response characteristics (such as voltage, etc.) of the battery aged according to the user may be updated to the battery model. The accuracy of the state information of the battery 110 estimated by the battery state estimation device 120 may be a relevant factor in the optimal management and control of the battery 110.

[0056] Figure 2 Shows an example electrochemical model according to one or more embodiments.

[0057] Referring to Figure 2 , in one non-limiting example, the electrochemical model may estimate the remaining capacity of the battery by modeling the internal physical phenomena of the battery 110 (such as the ion concentration, potential, etc. of the battery 110). In other words, the electrochemical model may be represented by physical conservation equations associated with the electrochemical reactions occurring at the electrode / electrolyte interface, the electrode / electrolyte concentration, and charge conservation. To this end, various model parameters (such as shape (e.g., thickness, radius, etc.), open circuit potential (OCP), and physical property values (e.g., conductance, ionic conductance, diffusion coefficient, etc.)) are used.

[0058] In the electrochemical model, different state variables (such as concentration and potential) may be coupled to each other. The estimated voltage 210 of the battery 110 estimated by the electrochemical model may be the potential difference between the two ends of the cathode and the anode. As shown by the arrow 220, the information about the potential of the cathode and the anode may be affected by the ion concentration distribution in each of the cathode and the anode. The SOC 230 estimated by the electrochemical model may correspond to the average ion concentration of the cathode and the anode.

[0059] Here, the ion concentration distribution can be the ion concentration distribution 240 in the electrode or the ion concentration distribution 250 in the active material particles at a predetermined position existing in the electrode. The ion concentration distribution 240 in the electrode can be the surface ion concentration distribution or the average ion concentration distribution of the active material particles in the electrode direction, and the electrode direction can be the direction connecting one end of the electrode (e.g., the boundary adjacent to the collector) and the other end of the electrode (e.g., the boundary adjacent to the separator). In addition, the ion concentration distribution 250 in the active material particles can be the ion concentration distribution inside the active material particles according to the central direction of the active material particles, and the central direction of the active material particles can be the direction connecting the center of the active material particles and the surface of the active material particles.

[0060] To reduce the voltage difference dV (e.g., sensed voltage - estimated voltage) between the measured voltage (or sensed voltage) and the estimated voltage of the battery 110, the ion concentration distributions of the cathode and the anode can be moved while maintaining the physical conservation associated with the concentration, information about the potential of each of the cathode and the anode can be obtained based on the moved concentration distributions, and the voltage can be calculated based on the obtained information about the potential of each of the cathode and the anode. The current SOC of the battery can be finally determined by obtaining the internal state movement amount that makes the voltage difference dV "0".

[0061] Figure 3 An example process of an operation compensator according to one or more embodiments is shown.

[0062] Referring to Figure 3 , in one non-limiting example, the anode potential (e.g., OCP) and the cell voltage (e.g., open circuit voltage (OCV)) in the fresh state where the battery is not aged and in the aged state where the battery is aged are shown.

[0063] The electrode balance shift is a characteristic in which the used area of the anode for determining the cathode - anode potential difference of the battery voltage is shifted, which may cause a change in the OCV characteristic of the battery, and the change in the OCV characteristic of the battery may be due to the change in the anode potential.

[0064] In other words, at low SOC, the cathode potential may show a slight difference between the fresh state and the aged state, while the anode potential may have a large difference between the fresh state and the aged state. The anode potential in the aged state can be in a shape shifted to the left from the anode potential in the fresh state, which can be referred to as "electrode balance shift".

[0065] The single-cell voltage curve indicates that the battery is being used and discharged. The difference between the voltage in the fresh state and the voltage in the aged state can be greater at a low state of charge (SOC) at the end of discharge than at a high SOC at the start of discharge. Specifically, a sharp change in the voltage difference between the fresh state and the aged state may occur at a low SOC. The reason can be found in the electrode balance shift.

[0066] When the battery model does not well reflect the current aging state because the actual battery ages due to its own electrode balance shift, Figure 3 the single-cell voltage curves of the fresh state and the aged state shown may not properly reflect the current aging state of the battery (such as the actual measured voltage). The difference between the estimated voltage of the electrochemical model and the actual measured voltage of the battery can be reduced by a compensator, and the operation of the compensator will be described in more detail below with reference to Figure 4 the operation of the compensator will be described in more detail below with reference to

[0067] Figure 4 An example compensator according to one or more embodiments is shown.

[0068] Referring to Figure 4 , in a non-limiting example, when a voltage difference (or error) occurs between the measured voltage and the estimated voltage of the battery 110 estimated by the battery model 410 (e.g., an electrochemical model), the compensator 420 can compensate for the internal state of the battery model 410 (e.g., an electrochemical model).

[0069] The battery state estimation device 120 can use the battery model 410 to determine (e.g., calculate or estimate) the state information of the battery 110. In one example, the battery model 410 can be a model that estimates the state information of the battery 110 by modeling the internal physical phenomena of the battery 110 (such as potential or ion concentration distribution).

[0070] The accuracy of estimating the state information of the battery 110 can affect the optimal management and control of the battery 110. When using the battery model 410 to estimate the state information, an error may occur between the value of the sensor information obtained from the current data, voltage data, and temperature data that will be input into the battery model 410 through measurement and the value of the state information calculated using the modeling scheme. In one example, the compensator 420 can compensate for this error when it occurs.

[0071] First, the voltage difference between the measured voltage of the battery 110 measured by the sensor and the estimated voltage of the battery 110 estimated by the battery model 410 can be determined.

[0072] In addition, the compensator 420 can determine the state change (or SOC error amount) of the battery 110 based on the determined voltage difference.

[0073] In one example, the compensator 420 may determine a state change (or SOC error amount) of the battery 110 based on the determined voltage difference, previously estimated state information through the battery model 410, and the OCV table. The compensator 420 may obtain the OCV corresponding to the previous state information based on the OCV table, and determine the state change of the battery 110 by reflecting the voltage difference to the obtained OCV.

[0074] In one example, the compensator 420 may use the surface concentration (e.g., stoichiometric concentration) of each electrode of the battery 110 estimated through the battery model 410 to determine the first OCP of each electrode of the battery 110. Then, the compensator 420 may use each determined first OCP to determine the first OCV of the battery 110. The compensator 420 may compensate the surface concentration of each electrode of the battery 110 based on the initial state change. The compensator 420 may use each compensated surface concentration to determine the second OCP of each electrode of the battery 110. Then, the compensator 420 may use each determined second OCP to determine the second OCV of the battery 110. The compensator 420 may use the determined first OCV, the determined second OCV, the initial state change, and the determined voltage difference to determine the state change of the battery 110. The compensator 420 may determine the difference between the "determined second OCV and the determined first OCV", and determine the state change of the battery 110 by applying the ratio between the determined difference and the determined voltage difference to the initial state change.

[0075] The compensator 420 may update the internal state of the battery model 410 based on the determined state change. For example, the internal state of the battery model 410 may include one of the voltage, overpotential, SOC, cathode lithium ion concentration distribution, anode lithium ion concentration distribution, and electrolyte lithium ion concentration distribution of the battery 110, or a combination of two or more of them, and may be in the form of a profile. The compensator 420 may update the internal state of the battery model 410 by compensating the ion concentration distribution in the active material particles or the ion concentration distribution in the electrodes based on the state change of the battery 110.

[0076] The battery state estimation device 120 may estimate the state information of the battery 110 based on the updated internal state of the battery model 410.

[0077] As described above, the battery state estimation device 120 may estimate the state information of the battery 110 with high accuracy through a feedback structure without increasing the complexity and computational amount of the model. The feedback structure updates the internal state of the battery model 410 by determining the state change of the battery 110 to minimize the voltage difference between the measured voltage of the battery 110 and the estimated voltage estimated through the battery model 410.

[0078] The operation of the compensator 420 described above can be used to estimate and update the electrode balance offset, which will be described in more detail below with reference to Figure 5 and will be described in more detail.

[0079] Figure 5 FIG. shows an example process of operating a compensator according to one or more embodiments.

[0080] Referring to Figure 5 , in a non-limiting example, the monomer voltages in the fresh state, the aged state, and the state in which SOC compensation is performed in the fresh state are shown.

[0081] In one example, when the battery model 410 estimates the state information (e.g., SOC) of the battery 110, the estimated voltage of the battery model 410 (e.g., Figure 5 the monomer voltage in the fresh state shown in ) can be compensated to match the measured voltage of the battery 110 (e.g., Figure 5 the monomer voltage in the aged state shown in ). At this time, the voltage difference between the measured voltage and the estimated voltage can be reduced by the SOC compensation of the battery model 410. The cumulative SOC compensation amount is a value used to compensate for the voltage difference caused by the electrode balance offset, and the battery state estimation device 120 can use "the degree to which the state information of the battery 110 is compensated by the compensator 420" to estimate and update the electrode balance offset as an aging parameter.

[0082] In one example, the cumulative SOC compensation amount can be determined based on "the degree 510 to which the monomer voltage in the fresh state will be compensated to the monomer voltage in the aged state by the compensator 420". Using the characteristic of determining the cumulative SOC compensation amount of the compensator 420 according to the aging degree of the battery 110, the battery state estimation device 120 can update the aging parameter (e.g., electrode balance offset) of the battery model 410 by converting the cumulative SOC compensation amount of the compensator 420 in a predetermined interval into an electrode balance offset value. The predetermined interval can be the region 520 where the voltage difference is compensated by the compensator 420, and for example, the starting point of the predetermined interval can be between 30% and 40% (including the end values) for the SOC of the battery 110, or between 0.3 and 0.4 (including the end values) for the anode stoichiometric concentration of the battery 110.

[0083] Therefore, the electrode balance shift can be determined based on the cumulative SOC compensation amount up to the full discharge time point, and the battery 110 can be charged first before the battery 110 reaches the full discharge time point according to the usage pattern of the user of the battery or the environment in which the battery is located. Here, the full discharge time point may correspond to the SOC value when the discharge cut-off voltage is reached during the standard discharge at room temperature. In one example, the electrode balance shift can be accurately estimated, where the cumulative SOC compensation amount at the full discharge time point can be estimated from the cumulative SOC compensation amount up to the discharge time point (e.g., partial discharge time point) before reaching the full discharge time point. The operation of estimating the cumulative SOC compensation amount at the full discharge time point from the cumulative SOC compensation amount at the partial discharge time point and using the cumulative SOC compensation amount to estimate the electrode balance shift will be described in more detail below with reference to the following drawings.

[0084] Figure 6 Shows an example process of determining a state of charge (SOC) compensation amount prediction curve graph according to one or more embodiments. Referring to Figure 6 , in a non-limiting example, the SOC compensation amount prediction curve graph 640 can be determined to estimate a second cumulative SOC compensation amount at the full discharge time point from a first cumulative SOC compensation amount at the partial discharge time point. In Figure 6 , for ease of description, the x-axis of the curve graph is represented as the anode stoichiometric concentration, but in one example, the x-axis can also be represented as the SOC. The anode stoichiometric concentration can correspond to the lithium concentration of the battery and can have an absolute value, while the SOC is a relative value and can have a specified position that can vary from 0% to 100% depending on the application or example.

[0085] When the battery ages due to the electrode balance shift, the SOC compensation amount prediction curve graph 640 can be determined based on the characteristic that the voltage difference between the cell voltage in the aged state (e.g., the estimated voltage of the battery model in the assumed aged state or the measured voltage of the aged battery) and the cell voltage in the fresh state (e.g., the estimated voltage of the electrochemical model that does not reflect aging) has a predetermined pattern. Aging due to the electrode balance shift can be a shift in the usage area of the anode, and the anode potential difference caused by the shift can be the same as the voltage compensated when estimating the electrode balance shift. In other words, the value of the electrode balance shift can correspond to the characteristic of the anode potential difference caused by the shift.

[0086] The range in which the electrode balance shift can be estimated is the region where the anodic potential difference increases significantly, and in one example, it can be the range where the anodic stoichiometric concentration X is 0.3 or less. In other words, the electrode balance shift can be estimated in the range of X < 0.3, and the range of X < 0.3 during 0.5C discharge can correspond to the range where the SOC is 40% or less. However, the starting point of the range in which the electrode balance shift can be estimated is not limited to X = 0.3, and in some examples, the starting point can be X = 0.3 to 0.4.

[0087] In one example, Figure 6 The voltage difference curve 620 based on aging shown in FIG. 6 shows the voltage difference between the anodic potential in the fresh state and the anodic potential in the aged state, which can be obtained from the anodic potential change curve 610 based on aging. The shape of the curve can be predetermined according to the battery in use. In other words, for batteries with the same characteristics (e.g., battery materials, etc.), the voltage difference curve 620 based on aging can have the same shape. The cumulative SOC compensation amount for estimating the electrode balance shift can be obtained by accumulating the SOC values used to compensate the voltage difference (or anodic potential difference), and when the voltage difference curve 620 based on aging is fixed, the cumulative SOC compensation amount for estimating the electrode balance shift can have a predetermined pattern.

[0088] The cumulative voltage difference curve 630 can be determined by accumulating the voltage differences starting from a predetermined time point in the voltage difference curve 620 based on aging. The predetermined time point is the time point when the voltage difference starts to gradually increase in the voltage difference curve 620 based on aging, and can be, for example, the time point when the anodic stoichiometric concentration X is between 0.3 and 0.4 (including the end values) as described above. Although the cumulative voltage difference curve 630 has a peak in the range of "anodic stoichiometric concentration is 0.50 to 0.55", it is difficult to predict the cumulative SOC compensation amount in this specific range. Therefore, the voltage differences during this range may not be accumulated.

[0089] Since the cumulative SOC compensation amount for estimating the electrode balance shift is based on the same characteristics as the characteristics of the cumulative voltage difference curve 630 corresponding to the cumulative SOC compensation amount, the SOC compensation amount prediction curve 640 can be determined from the cumulative voltage difference curve 630. In one example, the SOC compensation amount prediction curve 640 can be determined by normalizing the y-axis data range of the cumulative voltage difference curve 630. The cumulative voltage difference curve 630 is normalized to reduce the data usage for data processing, and in one example, the SOC compensation amount prediction curve 640 can be determined to be the same as the cumulative voltage difference curve 630.

[0090] Because the SOC compensation amount prediction curve 640 has a fixed pattern according to the battery characteristics, the SOC compensation amount prediction curve 640 can be determined in advance before estimating the electrode balance shift, and the predetermined SOC compensation amount prediction curve 640 can be simply applied when estimating the electrode balance shift.

[0091] Figure 7 An example process for estimating the cumulative SOC compensation amount according to one or more embodiments is shown. Referring to Figure 7 , in a non-limiting example, an example of estimating the second cumulative SOC compensation amount A2 at the full discharge time point from the first cumulative SOC compensation amount A1 at the partial discharge time point based on a predetermined SOC compensation amount prediction curve is shown.

[0092] The first cumulative SOC compensation amount A1 can be measured at the partial discharge time point. In one example, the partial discharge time point is an incompletely discharged time point when the anode stoichiometric concentration X is 0.3 or less, and can be a time point when the SOC is between 15% and 40% (including the end values), but is not limited thereto.

[0093] It can be at Figure 6 The third cumulative SOC compensation amount B1 corresponding to the battery state (e.g., anode stoichiometric concentration, SOC, etc.) at the partial discharge time point can be determined in the shown predetermined SOC compensation amount prediction curve. In addition, the fourth cumulative SOC compensation amount B2 corresponding to the battery state at the full discharge time point can be determined in the SOC compensation amount prediction curve. The battery state at the full discharge time point can be the SOC or anode stoichiometric concentration value when the discharge cut-off voltage is reached during standard discharge at room temperature.

[0094] In one example, the second cumulative SOC compensation amount A2 at the full discharge time point can be determined based on Equation 1 below.

[0095] Equation 1:

[0096]

[0097] The second cumulative SOC compensation amount A2 at the full discharge time point can be converted into an electrode balance shift value based on Equation 2 below.

[0098] Equation 2:

[0099] Electrode balance shift = A2 × (X SOC100％ - X SOC0％ )

[0100] In Equation 2 above, X SOC100％ can be the anode stoichiometric concentration value corresponding to 100% SOC, and X SOC0％It can be the anode stoichiometric concentration value corresponding to 0% SOC.

[0101] Figure 8 and Figure 9 illustrates an example process of determining a SOC compensation amount prediction curve graph according to one or more embodiments.

[0102] The above reference Figure 6 The operation of determining the SOC compensation amount prediction curve graph 640 described above can be based on the following assumption: The measured voltage of the actual fresh single cell is the same as or substantially similar to the estimated voltage of the electrochemical model in the fresh state. In other words, by applying the assumption that there is no model error or there is a relatively small model error, the anode potential change curve graph 610 can be used to determine the SOC compensation amount prediction curve graph 640.

[0103] Because in the absence of the above assumption, in one example, due to model error, the measured voltage of the actual fresh single cell is not the same as the estimated voltage of the battery model in the fresh state, so the model error can be reflected in the voltage difference curve graph used to determine the SOC compensation amount prediction curve graph, which will be described in more detail below.

[0104] Referring to Figure 8 , in a non-limiting example, a process of determining a second discharge voltage difference curve graph 830 reflecting model error is illustrated.

[0105] In one example, during low current discharge (e.g., 0.2C discharge), the discharge voltage curve graph 810 can be with respect to the measured voltage of the fresh single cell and the estimated voltage of the large capacity model. The large capacity model can be a model with a model capacity intentionally increased by adjusting the capacity parameter of the electrochemical model. For example, the capacity of the large capacity model can be about 102% of the capacity of the electrochemical model, but is not limited thereto.

[0106] When there is a voltage difference between the fresh single cell and the aged single cell due to aging caused by electrode balance shift, the electrochemical model may need to be updated. Here, the fresh single cell can correspond to a state that is less aged and has a larger battery capacity than the aged single cell, and the aged single cell can correspond to a state that is more aged (i.e., older and / or has experienced more use) and has a smaller battery capacity than the fresh single cell. To determine the voltage difference curve graph, data from a high capacity model with a larger battery capacity and a single cell with a relatively smaller battery capacity may be required. For example, when the anode moves in the negative direction during aging caused by electrode balance shift, the large capacity model can be achieved by shifting the anode in the positive direction by an amount corresponding to 2% SOC. Alternatively, the large capacity model can be achieved by magnifying the electrode area parameter in the model parameters to the level of 102%.

[0107] In one example, the first discharge voltage difference curve graph 820 may represent the difference between the measured voltage of a fresh single cell shown in the discharge voltage curve graph 810 and the estimated voltage of the large-capacity model. The first discharge voltage difference curve graph 820 starting from a predetermined time point can be used to determine the cumulative discharge voltage difference 920 as shown below Figure 9 As described above, the predetermined time point may be a time point when the SOC is between 30% and 40% (including the end values). However, in Figure 8 For ease of description, the predetermined time point may be determined as the time point when the SOC is 40%.

[0108] The second discharge voltage difference curve graph 830 only shows a part of the curve graph after the predetermined time point in the first discharge voltage difference curve graph 820 for the anode stoichiometric concentration, and an offset value can be applied to the voltage difference value at the predetermined time point to make the voltage difference value "0".

[0109] Referring to Figure 9 In a non-limiting example, a process of determining the SOC compensation amount prediction curve graph 930 from the second discharge voltage difference curve graph 910 is shown. The cumulative discharge voltage difference curve graph 920 can be determined by accumulating the voltage differences starting from a predetermined time point (for example, the anode stoichiometric concentration X = 0.3) in the second discharge voltage difference curve graph 910. The SOC compensation amount prediction curve graph 930 can be determined based on the cumulative discharge voltage difference curve graph 920. In one example, the SOC compensation amount prediction curve graph 930 can be determined by normalizing the y-axis data range of the cumulative discharge voltage difference curve graph 920. The cumulative discharge voltage difference curve graph 920 is normalized to reduce the data usage for data processing, and in one example, the SOC compensation amount prediction curve graph 930 can be determined to be the same as the cumulative discharge voltage difference curve graph 920.

[0110] Figure 10 An example of the voltage difference according to one or more embodiments is shown.

[0111] Referring to Figure 10 In a non-limiting example, the measured voltage 1010 of the battery 110 and the estimated voltage 1020 determined by a battery model (for example, an electrochemical model) are shown.

[0112] In Figure 10 In one example, the cumulative SOC compensation amount can be started to be accumulated when the anode stoichiometric concentration X of the battery 110 is 0.3. As described above, the battery state estimation device 120 can estimate the second cumulative SOC compensation amount at the fully discharged time point of the battery 110.

[0113] In one example, a voltage difference may occur at the start of the interval during which the SOC compensation amount is accumulated. In one example, at the start of the interval during which the SOC compensation amount is accumulated, the estimated voltage 1020 may be greater than the measured voltage 1010. In one example, different from the example shown in Figure 10 at the start of the interval during which the SOC compensation amount is accumulated, the measured voltage 1010 may be greater than the estimated voltage 1020. When there is a voltage difference at the start of the interval during which the SOC compensation amount is accumulated, the second accumulated SOC compensation amount may reflect the SOC error amount corresponding to the voltage difference.

[0114] In one example, a battery state estimation device (e.g., the battery state estimation device 120) may determine whether a start condition for determining the SOC error amount is satisfied. Here, the start condition may include, for example, the condition that the anode stoichiometric concentration X of the battery 110 is a predetermined concentration value (e.g., 0.3) or the condition that the SOC of the battery 110 is a predetermined SOC value (e.g., 0.4). When the start condition is satisfied, the battery state estimation device may determine the voltage difference between the measured voltage 1010 and the estimated voltage 1020, and determine the SOC error amount at the start time point (e.g., the time point when the start condition is satisfied) based on the determined voltage difference. The battery state estimation device may estimate the second accumulated SOC compensation amount at the fully discharged time point of the battery, and adjust the second accumulated SOC compensation amount based on the determined SOC error amount. As will be described in more detail below, the battery state estimation device may estimate the aging parameter of the battery model based on the adjusted second accumulated SOC compensation amount. Therefore, the battery state estimation device may more accurately estimate the aging parameter of the battery model. The method for estimating the battery state will be described below with reference to Figure 11 a method for estimating the battery state is described.

[0115] Figure 11 FIG. shows an example method for estimating the battery state according to one or more embodiments.

[0116] Referring to Figure 11 , in a non-limiting example, in operation 1101, a battery state estimation device (e.g., the battery state estimation device 120) may measure a battery (e.g., the battery 110). For example, the battery state estimation device may measure one of the voltage, current, and temperature of the battery, or a combination of two or more of them. The measurement data may be in the form of a profile indicating the change in magnitude over time.

[0117] In operation 1102, the battery state estimation device may determine one of the estimated voltage and state information (e.g., SOC, RSOC, SOH, etc.) of the battery through a battery model (e.g., an electrochemical model), or a combination of two of the state information (e.g., SOC, RSOC, SOH, etc.). In one example, the battery model may consider one of the current and temperature measured in operation 1101, or a combination of the current and temperature measured in operation 1101.

[0118] In operation 1103, the battery state estimation device may compensate for one or a combination of two of the internal states of the battery model by the compensator 420 based on the voltage difference dV between the measured voltage and the estimated voltage.

[0119] In operation 1104, the battery state estimation device may determine whether the state of the battery (e.g., the aging state, etc.) corresponds to the detection interval of the aging parameter (e.g., the electrode balance shift) of the battery model. In one example, when the anode concentration of the battery (e.g., the stoichiometric concentration (anode stoichiometric concentration)) is less than or equal to a predetermined concentration value (e.g., 0.3) and / or when the SOC determined in operation 1102 is less than or equal to a predetermined SOC value (e.g., 0.4), the battery state estimation device may determine that the state of the battery corresponds to the detection interval of the aging parameter.

[0120] When the battery state estimation device determines that the state of the battery corresponds to the detection interval of the aging parameter, in operation 1105, the battery state estimation device may determine whether the start condition (e.g., the condition for starting operation 1106) is satisfied. The start condition may include, for example, the condition that the anode concentration of the battery (e.g., the anode stoichiometric concentration) is a predetermined concentration value (e.g., 0.3) and / or the condition that the state information of the battery (e.g., SOC) is a predetermined SOC value (e.g., 0.4). When the anode concentration of the battery (e.g., the anode stoichiometric concentration) is a predetermined concentration value (e.g., 0.3), the battery state estimation device may determine that the start condition is satisfied and then execute operation 1106. When the anode concentration of the battery (e.g., the surface concentration) is less than the predetermined concentration value (e.g., 0.3), the battery state estimation device may determine that the start condition is not satisfied and then execute operation 1107. When the SOC value of the battery is a predetermined SOC value (e.g., 0.4), the battery state estimation device may determine that the start condition is satisfied and execute operation 1106. When the SOC value of the battery is less than the predetermined SOC value (e.g., 0.4), the battery state estimation device may determine that the start condition is not satisfied and execute operation 1107.

[0121] When the battery state estimation device determines that the start condition is satisfied, in operation 1106, the battery state estimation device may determine the amount of SOC error at the time point when the start condition is satisfied (for example, the time point when the anode surface concentration of the battery is a predetermined concentration value or the time point when the SOC value of the battery is a predetermined SOC value). In one example, the battery state estimation device may determine the voltage difference dV at the time point when the start condition is satisfied, and determine the amount of SOC error at the time point when the start condition is satisfied based on the voltage difference dV at the time point when the start condition is satisfied. The battery state estimation device may determine the amount of SOC error at the time point when the start condition is satisfied as an offset value for adjusting the second cumulative SOC compensation amount. The method for determining the amount of SOC error at the time point when the start condition is satisfied will be described in more detail below.

[0122] When it is determined that the start condition is not satisfied, in operation 1107, the battery state estimation device may obtain the first cumulative SOC compensation amount at the partial discharge time point. In other words, when it is determined that the start condition is not satisfied although the state of the battery is within the detection range of the aging parameter, in operation 1107, the battery state estimation device may obtain the first cumulative SOC compensation amount at the partial discharge time point.

[0123] In operation 1108, the battery state estimation device may estimate the second cumulative SOC compensation amount at the full discharge time point based on the SOC compensation amount prediction curve and the first cumulative SOC compensation amount.

[0124] In operation 1109, the battery state estimation device may adjust the second cumulative SOC compensation amount based on the amount of SOC error (for example, the amount of SOC error or offset value determined in operation 1106). The battery state estimation device may adjust the second cumulative SOC compensation amount by reflecting (or applying) the offset value to the second cumulative SOC compensation amount. In one example, when the measured voltage (or sensed voltage) is less than the estimated voltage, in operation 1106, the battery state estimation device may determine the first offset value. The battery state estimation device may adjust the second cumulative SOC compensation amount by adding the first offset value to the second cumulative SOC compensation amount. In one example, when the measured voltage (or sensed voltage) is greater than the estimated voltage, in operation 1106, the battery state estimation device may determine the second offset value. The battery state estimation device may adjust the second cumulative SOC compensation amount by subtracting the second offset value from the second cumulative SOC compensation amount.

[0125] In operation 1110, the battery state estimation device may estimate the aging parameter of the battery model based on the adjusted second cumulative SOC compensation amount. In one example, when the time point is defined as n, the battery state estimation device may calculate the aging parameter value at time point n based on the adjusted second cumulative SOC compensation amount (i.e., as will be described below with reference to Figure 16A described in more detail n (e.g., the electrode balance offset value).

[0126] In operation 1111, the battery state estimation device may store the estimated aging parameter (e.g., the calculated aging parameter value) in a memory. In one example, the memory may be an internal memory of the battery state estimation device (e.g., memory 1920) or an external memory connected to the battery state estimation device via a wired network and / or a wireless network.

[0127] In operation 1112, the battery state estimation device may determine whether an update condition for the aging parameter is met. This will be described in more detail below with reference to Figure 16 When the update condition is met, the battery state estimation device may perform operation 1113. When the update condition is not met, the battery state estimation device may perform operation 1102.

[0128] In operation 1113, the battery state estimation device may reflect the aging parameter in the battery model. The battery state estimation device may use one or more aging parameter values stored in the memory to update the electrode balance offset value of the battery model. This will be described in more detail below with reference to Figure 16 In one example, some or all of the model parameters of the battery model may affect each other such that a change in one model parameter may affect other model parameters. The battery state estimation device may also update model parameters other than the electrode balance offset value of the battery model based on the electrode balance offset value.

[0129] Returning to operation 1104, the battery state estimation device may determine that the state of the battery does not correspond to the detection interval of the aging parameter. In this case, in operation 1114, the battery state estimation device may determine whether a termination condition is met. In one example, the battery state estimation device may determine whether the termination condition is met based on whether a predetermined operation time has elapsed. When the predetermined operation time has not elapsed, the battery state estimation device may perform operation 1101. When the predetermined operation time has elapsed, the battery state estimation device may terminate the operation of estimating the battery state.

[0130]

[0131]

[0132] Through the operations of the battery state estimation device as described above, even when the battery is not fully discharged according to the usage pattern or environment of battery 110, the electrode balance offset value can be accurately estimated and reflected in the battery model.​With an electrochemical model that reflects the actual aging state of the battery 110, it is possible to estimate the state information of the battery with high accuracy even in the aging state, and effectively suppress the aging accelerated by rapid charging or discharging through accurate state diagnosis of the battery 110, which can thus improve the safety of the battery 110.

[0133] For a more detailed description of the operations described with reference to Figure 11 refer to the content already described with reference to Figures 1 to 10 above.

[0134] Figure 12 and Figure 13 FIG. shows an example process of determining the SOC error amount by the battery state estimation device according to one or more embodiments. In one example, with reference to Figure 12 and Figure 13 the operations described can be included in Figure 11 operation 1106.

[0135] Referring to Figure 12 , in a non-limiting example, at a start time point (e.g., the time point when the anode concentration of the battery is a predetermined concentration value or the SOC of the battery is a predetermined SOC value), the sensed voltage (or measured voltage) of the battery 110 can be greater than the estimated voltage estimated by the battery model (e.g., the electrochemical model). In one example, when the sensed voltage is greater than the estimated voltage, the voltage difference dV can be a positive number.

[0136] In Figure 11 operation 1102, the battery state estimation device 120 can determine the SOC of the battery 110 (hereinafter referred to as SOC1) through the battery model.

[0137] Figure 12 The graph 1210 of

[0138] can represent the graph between the SOC and the OCV of the battery 110 and can represent the unique characteristics of the battery 110. The OCV table can correspond to the graph 1210. Figure 12 The battery state estimation device 120 can determine the OCV corresponding to the SOC1 determined by the battery model (hereinafter referred to as "OCV1") through the OCV table (or the graph 1210). The battery state estimation device 120 can reflect the voltage difference dV at the start time point in the OCV1. In one example, the battery state estimation device 120 can reflect the voltage difference dV in the OCV1 by adding the voltage difference dV to the OCV1. In the example shown in

[0139] The battery state estimation device 120 can use the OCV table (or the graph 1210) to determine the SOC corresponding to OCV2 (hereinafter referred to as "SOC2"). In Figure 12 the example shown, SOC2 can correspond to the SOC obtained by compensating SOC1 by the battery state estimation device 120. The battery state estimation device 120 can determine the difference between SOC2 and SOC1 as the SOC error amount at the start time point, and determine the determined SOC error amount as an offset value (for example, the second offset value described in operation 1109 of Figure 11 ).

[0140] Referring to Figure 13 , in a non-limiting example, the sensed voltage (or measured voltage) of the battery 110 at the start time point can be less than the estimated voltage estimated by the battery model. In this case, the voltage difference dV can be, for example, negative.

[0141] The battery state estimation device 120 can determine OCV1 corresponding to SOC1 determined by the battery model through the OCV table (or the graph 1210). The battery state estimation device 120 can reflect the voltage difference dV at the start time point in OCV1. In Figure 13 the example shown, the sensed voltage can be less than the estimated voltage, and thus, the OCV reflecting the voltage difference dV (hereinafter referred to as "OCV3") (for example, OCV3 = OCV1 + dV) can be less than OCV1.

[0142] The battery state estimation device 120 can use the OCV table (or the graph 1210) to determine the SOC corresponding to OCV3 (hereinafter referred to as "SOC3"). In Figure 13 the example shown, SOC3 can correspond to the SOC obtained by compensating SOC1 by the battery state estimation device 120. The battery state estimation device 120 can determine the difference between SOC3 and SOC1 as the SOC error amount at the start time point, and determine the determined SOC error amount as an offset value (for example, the first offset value described in operation 1109 of Figure 11 ).

[0143] Figure 14 and Figure 15 show example processes for determining the SOC error amount by the battery state estimation device according to one or more embodiments. The operations described with reference to Figure 14 and Figure 15 can be included in operation 1106 of Figure 11 .

[0144] In a non-limiting example, Figure 14 and Figure 15Figure 1410 corresponding to the first OCP table and Figure 1420 corresponding to the second OCP table are shown. The first OCP table may correspond to, for example, an OCP table representing the relationship between the cathode stoichiometric concentration of battery 110 and the OCP. Figure 1410 may represent a curve (or graph) of the OCP according to the cathode stoichiometric concentration of battery 110. The second OCP table may correspond to, for example, an OCP table representing the relationship between the anode stoichiometric concentration of battery 110 and the OCP. Figure 1420 may represent a curve (or graph) of the OCP according to the anode stoichiometric concentration of battery 110.

[0145] In one example, the stoichiometric concentration may have an absolute value, while the SOC is a relative value and may have a specified position that can vary from 0% to 100% depending on the application.

[0146] In Figure 14 the example shown, the battery state estimation device 120 may determine the surface concentration of each electrode of battery 110, the estimated voltage of battery 110, and the SOC of battery 110 (hereinafter referred to as "SOC1" in Figure 14 ). In Figure 11 operation 1102 of, the battery state estimation device 120 may determine the surface concentration of each electrode of battery 110, the estimated voltage of battery 110, and SOC1. In Figure 14 the example shown, the battery state estimation device 120 may determine the cathode surface concentration of battery 110 as Y1 and the anode surface concentration of battery 110 as X1.

[0147] The battery state estimation device 120 may determine the voltage difference dV between the sensed voltage of battery 110 and the estimated voltage of battery 110. In one example, the estimated voltage may be 300 mV less than the sensed voltage. The battery state estimation device 120 may calculate the voltage difference dV as 300 mV according to "sensed voltage - estimated voltage". A positive value of the voltage difference dV (e.g., 300 mV) may mean that the battery model determines through the internal state (e.g., at least one parameter) of the battery model that SOC1 is less than the actual SOC of battery 110 (e.g., the SOC of battery 110 in a state where various errors such as sensor errors and battery model errors are excluded).

[0148] The battery state estimation device 120 may obtain the OCP value (e.g., 3.95 V) corresponding to the cathode surface concentration Y1 from the first OCP table (or Figure 1410). The battery state estimation device 120 may obtain the OCP value (e.g., 0.17 V) corresponding to the anode surface concentration X1 from the second OCP table (or Figure 1420).

[0149] The battery state estimation device 120 may calculate the difference (e.g., 3.78 V) between the OCP value (e.g., 3.95 V) corresponding to the cathode surface concentration Y1 and the OCP value (e.g., 0.17 V) corresponding to the anode surface concentration X1. The battery state estimation device 120 may determine the calculated difference (e.g., 3.78 V) as the OCV1 of the battery 110. In one example, the OCV1 may correspond to the OCV of the battery 110 at SOC1.

[0150] The battery state estimation device 120 may determine the concentration movement amount (or concentration change) of the electrodes (e.g., Figure 14 dY1411 and dX1421). The cathode concentration movement amount (or concentration change) dY1411 may indicate, for example, the degree to which the cathode surface concentration Y1 will move (or change) in the graph 1410. The anode concentration movement amount (or concentration change) dX1421 may indicate, for example, the degree to which the anode surface concentration X1 will move (or change) in the graph 1420. The surface concentration of each electrode may be compensated by the concentration movement amount (or concentration change) of each electrode, and thus the concentration movement amount may be expressed as a compensation value (or concentration compensation amount). The compensation value (or concentration compensation amount) of each electrode may indicate the degree to which the surface concentration of each electrode will be compensated.

[0151] The battery state estimation device 120 may determine the concentration movement amount (or compensation value) dY1411 for compensating the cathode surface concentration Y1 based on the initial SOC error amount (or initial state change) d_SOC_0. The battery state estimation device 120 may determine the concentration movement amount (or compensation value) dX1421 for compensating the anode surface concentration X1 based on the initial SOC error amount d_SOC_0. For example, the initial SOC error amount d_SOC_0 may have a fixed value, but the example is not limited thereto. In one example, the battery state estimation device 120 may determine the initial SOC error amount d_SOC_0 through the voltage difference dV and the OCV table (or graph 1210).

[0152] In one example, the battery state estimation device 120 may use the initial SOC error amount d_SOC_0 and the predetermined value d_SOC_CA for the cathode of the battery 110 to determine dY1411 (e.g., dY = d_SOC_0 × d_SOC_CA). The battery state estimation device 120 may use the initial SOC error amount d_SOC_0 and the predetermined value d_SOC_AN for the anode of the battery 110 to determine dX1421 (e.g., dX = d_SOC_0 × d_SOC_AN). In Figure 14In the case of the example shown, as will be described in more detail below, the voltage difference dV can be positive, d_SOC_CA can be negative, and d_SOC_AN can be positive. Thus, the relationship "dY 1411 < 0" can be satisfied, and the relationship "dX 1421 > 0" can be satisfied. dY 1411 can be the direction in which the cathode concentration (e.g., cathode surface concentration or stoichiometric concentration) decreases, and dX 1421 can be the direction in which the anode concentration (e.g., anode surface concentration or stoichiometric concentration) increases.

[0153] The predetermined value d_SOC_CA for the cathode can 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% can be 0.3, and the cathode concentration corresponding to SOC = 0% can be 0.9. In this case, the predetermined value d_SOC_CA for the cathode can be -0.6.

[0154] The predetermined value d_SOC_AN for the anode can represent, for example, the difference between the anode concentration corresponding to SOC = 100% and the anode concentration corresponding to SOC = 0%. In one example, the anode concentration corresponding to SOC = 100% can be 0.9, and the anode concentration corresponding to SOC = 0% can be 0.01. In this case, the predetermined value d_SOC_AN for the anode can be 0.89.

[0155] The battery state estimation device 120 can compensate the cathode surface concentration Y1 by dY 1411. The compensated cathode surface concentration Y1 + dY can correspond to the position where the cathode surface concentration Y1 is shifted by dY 1411 on the graph 1410. The compensated cathode surface concentration Y1 + dY can be less than the cathode surface concentration Y1. The battery state estimation device 120 can obtain the OCP value (e.g., 4.1V) corresponding to the compensated (or shifted) cathode surface concentration Y1 + dY in the first OCP table (or graph 1410).

[0156] The battery state estimation device 120 can compensate the anode surface concentration X1 by dX 1421. The compensated anode surface concentration X1 + dX can correspond to the position where the anode surface concentration X1 is shifted by dX 1421 on the graph 1420. The compensated anode surface concentration X1 + dX can be greater than the anode surface concentration X1. The battery state estimation device 120 can obtain the OCP value (e.g., 0.13V) corresponding to the compensated (or shifted) anode surface concentration X1 + dX in the second OCP table (or graph 1420).

[0157] In one example, the battery state estimation device 120 may calculate the difference (e.g., 3.97 V) between the OCP value corresponding to the compensated cathode surface concentration (e.g., 4.1 V) and the OCP value corresponding to the compensated anode surface concentration (e.g., 0.13 V). The battery state estimation device 120 may determine the calculated difference (e.g., 3.97 V) as the OCV2 of the battery 110.

[0158] The battery state estimation device 120 may use the initial SOC error amount d_SOC_0, the OCV1 of the battery 110, the OCV2 of the battery 110, and the voltage difference dV to determine the SOC error amount d_SOC of the battery 110. In one example, the battery state estimation device 120 may determine the SOC error amount d_SOC of the battery 110 through Equation 3 below.

[0159] Equation 3:

[0160] d_SOC_0:d_SOC = OCV difference:dV

[0161] In one example, absolute values may be applied to the OCV difference and / or dV in Equation 3 above.

[0162] The ratio between d_SOC_0 and d_SOC may be equal to the ratio between the OCV difference (e.g., OCV2 - OCV1 = 3.97 V - 3.78 V = 0.19 V) and the voltage difference dV. When d_SOC_0 is, for example, 3%, d_SOC may also be "3% × 0.3 / 0.19 = 4.73%". In other words, the battery state estimation device 120 may determine d_SOC as 4.73% by applying d_SOC_0 to the ratio between the OCV difference and the voltage difference dV. The battery state estimation device 120 may determine the determined d_SOC (e.g., 4.73%) as the offset value (e.g., the second offset value described in Figure 11 operation 1109).

[0163] Unlike the example shown in Figure 14 , in the example shown in Figure 15 , the estimated voltage may be greater than the sensed voltage. An example of the battery state estimation device 120 determining the SOC error amount when the estimated voltage is greater than the sensed voltage will be described below with reference to Figure 15 .

[0164] Referring to Figure 15 , in a non-limiting example, the battery state estimation device 120 may determine the surface concentration of each electrode of the battery 110, the estimated voltage of the battery 110, and the SOC of the battery 110 (hereinafter referred to as "SOC2" in Figure 15 ) through a battery model. In Figure 15In the example shown, the battery state estimation device 120 may determine the cathode surface concentration of the battery 110 as Y1, and determine the anode surface concentration of the battery 110 as X1.

[0165] In one example, the battery state estimation device 120 may determine the voltage difference dV between the sensed voltage of the battery 110 and the estimated voltage of the battery 110. For example, the estimated voltage may be 200 mV greater than the sensed voltage. The battery state estimation device 120 may calculate the voltage difference dV as -200 mV based on "sensed voltage - estimated voltage". The negative value of the voltage difference dV (e.g., -200 mV) may mean that the battery model determines through the internal state of the battery model that: SOC2 is greater than the actual SOC of the battery 110.

[0166] The battery state estimation device 120 may obtain the OCP value (e.g., 3.95 V) corresponding to the cathode surface concentration Y1 from the first OCP table (or graph 1410). The battery state estimation device 120 may obtain the OCP value (e.g., 0.17 V) corresponding to the anode surface concentration X1 from the second OCP table (or graph 1420).

[0167] The battery state estimation device 120 may calculate the difference (e.g., 3.78 V) between the OCP value (e.g., 3.95 V) corresponding to the cathode surface concentration Y1 and the OCP value (e.g., 0.17 V) corresponding to the anode surface concentration X1. The battery state estimation device 120 may determine the calculated difference (e.g., 3.78 V) as the OCV1 of the battery 110.

[0168] When the voltage difference dV is negative, the battery state estimation device 120 may change (or convert) the sign of the initial state change d_SOC_0. For example, d_SOC_0 may be 3%. When the voltage difference dV is positive, the battery state estimation device 120 may use d_SOC_0 without the above-mentioned sign change (or sign conversion). When the voltage difference dV is negative, the battery state estimation device 120 may change (or convert) d_SOC_0 to -3% through a sign change (or sign conversion).

[0169] The battery state estimation device 120 may determine the compensation value (or concentration shift amount) dY 1511 for compensating the cathode surface concentration Y1 based on the changed initial SOC error amount -d_SOC_0. The battery state estimation device 120 may determine the compensation value (or concentration shift amount) dX1521 for compensating the anode surface concentration X1 based on the changed initial SOC error amount -d_SOC_0.

[0170] In one example, the battery state estimation device 120 may use the changed initial SOC error amount -d_SOC_0 and a predetermined value d_SOC_CA for the cathode of the battery 110 to determine dY 1511 (e.g., dY = -d_SOC_0 × d_SOC_CA). The battery state estimation device 120 may use the changed initial SOC error amount -d_SOC_0 and a predetermined value d_SOC_AN for the anode of the battery 110 to determine dX 1521 (e.g., dX = -d_SOC_0 × d_SOC_AN). Since the voltage difference dV is negative, dY 1511 may be in the direction in which the cathode concentration (e.g., cathode surface concentration or stoichiometric concentration) increases, and dX 1521 may be in the direction in which the anode concentration (e.g., anode surface concentration or stoichiometric concentration) decreases.

[0171] The battery state estimation device 120 may compensate the cathode surface concentration Y1 by dY 1511. The compensated cathode surface concentration Y1 + dY may be greater than the cathode surface concentration Y1. The battery state estimation device 120 may obtain the OCP value (e.g., 3.91V) corresponding to the compensated cathode surface concentration Y1 + dY in the first OCP table (or graph 1410). The battery state estimation device 120 may compensate the anode surface concentration X1 by dX 1521. The compensated anode surface concentration X1 + dX may be less than the anode surface concentration X1. The battery state estimation device 120 may obtain the OCP value (e.g., 0.21V) corresponding to the compensated anode surface concentration X1 + dX in the second OCP table (or graph 1420).

[0172] The battery state estimation device 120 may calculate the difference (e.g., 3.7V) between the OCP value (e.g., 3.91V) corresponding to the compensated cathode surface concentration and the OCP value (e.g., 0.21V) corresponding to the compensated anode surface concentration. The battery state estimation device 120 may determine the calculated difference (e.g., 3.7V) as the OCV3 of the battery 110.

[0173] The battery state estimation device 120 can use the changed initial SOC error amount -d_SOC_0, the OCV1 of the battery 110, the OCV3 of the battery 110, and the voltage difference dV to determine the SOC error amount d_SOC of the battery 110. In one example, the battery state estimation device 120 can determine the SOC error amount d_SOC of the battery 110 through Equation 3 above. According to Equation 3 above, the ratio between -d_SOC_0 and d_SOC can be equal to the ratio between the OCV difference (for example, OCV3 - OCV1 = 3.7V - 3.78V = -0.08V) and the voltage difference dV. When -d_SOC_0 is, for example, -3%, d_SOC can be "-3% × (-0.2) / (-0.08) = -7.5%". In other words, in Figure 15 the example shown, the battery state estimation device 120 can determine d_SOC as -7.5%. The battery state estimation device 120 can determine the determined d_SOC (for example, -7.5%) as an offset value (for example, the first offset value described in Figure 11 operation 1109 of

[0174] Figure 16 FIG. shows an example method for updating aging parameters according to one or more embodiments.

[0175] Referring to Figure 16 , in a non-limiting example, the calculated aging parameter value can be stored in the memory each time the aging parameter value is calculated, and one or more aging parameter values can be used to update the aging parameter of the electrochemical model when the update condition is reached, rather than immediately updating the aging parameter of the battery model based on the calculated aging parameter value. In Figure 16 , A n-1 , A n , …, A n+3 can be the sequentially calculated aging parameter values. Figure 16 The A n-1 , A n , …, A n+3 in each is the electrode balance offset value calculated each time the above operation 1110 is performed, and may not have been reflected in the electrochemical model yet.

[0176] In Figure 16 the example shown, the update condition can be reached after calculating the aging parameter value A n+3 . In this case, the final parameter value A* to be used for updating the aging parameter can be determined based on one or more aging parameter values stored in the memory. In one example, the final parameter value A* can be determined as the aging parameter values A n ,... and A between the current time point when the update condition is reached and the nearest time point (for example, the time point when the update condition was last reached)n+3 statistical values (e.g., average value, moving average value, median value, maximum value, etc.). The battery state estimation device 120 may apply the final parameter value A* to the aging parameter (e.g., electrode balance shift) of the battery model. Optionally, the final parameter value A* may be determined as a statistical value of the n aging parameter values calculated most recently based on the current time point when the update condition is met (n is a natural number greater than 0). Depending on the situation (e.g., when n is "5"), the aging parameter values (e.g., A n-1 ) used to determine the previous aging parameter may also be used for this update.

[0177] In one example, the update condition may be determined based on one of the number of charge-discharge cycles of the battery, the cumulative used capacity of the battery, the cumulative used time of the battery, and the number of aging parameter values stored in the memory, or a combination of two or more of them. In one example, in order to update the aging parameter of the electrochemical model using multiple aging parameter values accumulated when the battery is charged and discharged multiple times, one of the number of charge-discharge cycles of the battery, the cumulative used capacity of the battery, the cumulative used time of the battery, and the number of aging parameters stored in the memory, or a combination of two or more of them, may be used as the update condition. However, the update condition is not limited to this.

[0178] In one example, the battery state estimation device 120 may store the adjusted second cumulative SOC compensation amount in the memory (e.g., memory 1730) each time the second cumulative SOC compensation amount is adjusted. When the update condition is met, the battery state estimation device 120 may calculate the average value of one or more adjusted second cumulative SOC compensation amounts stored in the memory, and apply or reflect the calculated average value to the aging parameter (e.g., electrode balance shift) of the battery model. In one example, the battery state estimation device 120 may store the adjusted second cumulative SOC compensation amount at time point a (hereinafter, S a ) in the memory, and store the adjusted second cumulative SOC compensation amount at time point a + 1 (hereinafter, S a+1 ) in the memory. The battery state estimation device 120 may store the adjusted second cumulative SOC compensation amount at time point a + n (hereinafter, referred to as S a+n ). When the update condition is met, the battery state estimation device 120 may calculate the average value of the adjusted second cumulative SOC compensation amounts S a ,..., S a+n stored in the memory. The battery state estimation device 120 may convert the calculated average value into the electrode balance shift value of the battery model through the above equation 2. The battery state estimation device 120 may apply or reflect the converted electrode balance shift value to the battery model. As a result, the electrode balance shift of the battery model may be updated.

[0179] Figure 17 An example of an electronic device according to one or more embodiments is shown.

[0180] Referring Figure 17 , in a non - limiting example, the battery state estimation device 120 may include a processor 1710, a voltage sensor 1720, and a memory 1730.

[0181] The memory 1730 may include computer - readable instructions. The processor 1710 may be configured to execute the computer - readable instructions (such as the computer - readable instructions stored in the memory 1730), and by executing the computer - readable instructions, the processor 1710 is configured to perform one or more or any combination of the operations and / or methods described herein. The memory 1730 may be a volatile memory or a non - volatile memory. In one example, the memory 1730 may store a battery model (e.g., an electrochemical model).

[0182] In one example, the processor 1710 may determine a voltage difference dV between an estimated voltage of the battery 110 determined by the battery model and a sensed voltage (or measured voltage) of the battery 110 obtained using the voltage sensor 1720. The processor 1710 may determine whether a start condition for determining the SOC error amount is satisfied. At this time, when the anode concentration of the battery 110 (e.g., the anode surface concentration determined by the battery model) has reached a predetermined concentration value or when the SOC of the battery 110 (e.g., the SOC determined by the battery model) has reached a predetermined SOC value, the processor 1710 may determine that the start condition is satisfied. When the processor 1710 determines that the start condition is satisfied, the processor 1710 may determine the voltage difference at the time point when the start condition is satisfied.

[0183] The processor 1710 can determine the amount of SOC error of the battery 110 based on the determined voltage difference. In one example, the processor 1710 can obtain the OCV corresponding to the SOC of the battery determined by the battery model from the OCV table. The processor 1710 can determine the amount of SOC error of the battery 110 by reflecting the determined voltage difference in the obtained OCV. In one example, the processor 1710 can use the surface concentration of each electrode of the battery 110 to determine the first OCP of each electrode of the battery 110. The processor 1710 can use each determined first OCP to determine the first OCV of the battery 110. The processor 1710 can compensate each surface concentration based on the initial SOC error amount. The processor 1710 can use each compensated surface concentration to determine the second OCP of each electrode of the battery 110. The processor 1710 can use each determined second OCP to determine the second OCV of the battery 110. The processor 1710 can use the determined first OCV, the determined second OCV, the initial SOC error amount, and the determined voltage difference to determine the amount of SOC error of the battery 110. The processor 1710 can determine the determined amount of SOC error as an offset value.

[0184] The processor 1710 can determine a first cumulative SOC compensation amount, which is the cumulative SOC compensation amount for compensating the SOC of the battery 110 at a partial discharge time point of the battery 110.

[0185] The processor 1710 can estimate a second cumulative SOC compensation amount at a full discharge time point of the battery 110 based on the determined first cumulative SOC compensation amount and a predetermined SOC compensation amount prediction curve. In one example, the processor 1710 can obtain a third cumulative SOC compensation amount corresponding to the battery state (e.g., partial discharge battery state) at the partial discharge time point in the SOC compensation amount prediction curve. The processor 1710 can obtain a fourth cumulative SOC compensation amount corresponding to the battery state (e.g., full discharge battery state) at the full discharge time point in the SOC compensation amount prediction curve. The processor 1710 can use the determined first cumulative SOC compensation amount, the obtained third cumulative SOC compensation amount, and the obtained fourth cumulative SOC compensation amount to estimate the second cumulative SOC compensation amount.

[0186] The processor 1710 may adjust the estimated second cumulative SOC compensation amount based on the SOC error amount (or the determined offset value) at the time point when the start condition is satisfied. For example, the processor 1710 may adjust the estimated second cumulative SOC compensation amount by subtracting the SOC error amount (or the offset value) (e.g., the second offset value) at the time point when the start condition is satisfied from the estimated second cumulative SOC compensation amount. In one example, the processor 1710 may adjust the estimated second cumulative SOC compensation amount by adding the estimated second cumulative SOC compensation amount to the SOC error amount (or the offset value) (e.g., the first offset value). The first offset value and the second offset value may be, for example, positive numbers.

[0187] In one example, the processor 1710 may update the aging parameter of the battery model based on the adjusted second cumulative SOC compensation amount. In one example, the processor 1710 may store the aging parameter value calculated based on the adjusted second cumulative SOC compensation amount in the memory 1730. According to an embodiment, the aging parameter value may be stored in a memory other than the memory 1730. When the update condition of the aging parameter is satisfied, the processor 1710 may use one or more aging parameter values stored in the memory 1730 to update the aging parameter of the battery model. For example, the processor 1710 may calculate the average value of one or more aging parameter values (e.g., the electrode balance offset value) stored in the memory 1730, and reflect or apply the calculated average value to the aging parameter (e.g., the electrode balance offset) of the battery model. Thus, the processor 1710 may update the electrode balance offset of the battery model. In one example, the processor 1710 may store the adjusted second cumulative SOC compensation amount in the memory 1730. According to an embodiment, the adjusted second cumulative SOC compensation amount may be stored in a memory other than the memory 1730. When the update condition of the aging parameter is satisfied, the processor 1710 may calculate the average value of multiple adjusted second cumulative SOC compensation amounts stored in the memory 1730, and use the calculated average value to update the aging parameter of the battery model. In one example, the processor 1710 may calculate the electrode balance offset value by multiplying the difference between X SOC100％ and X SOC0％ by the average value of multiple adjusted second cumulative SOC compensation amounts, and reflect or apply the calculated electrode balance offset value to the electrode balance offset of the battery model. Thus, the processor 1710 may update the electrode balance offset of the battery model.

[0188] The processor 1710 may be configured to execute a program or an application to configure the processor 1710 to control the battery state estimation device 120 to perform one or more or all operations and / or methods related to battery state estimation, and may include, for example, any one of a central processing unit (CPU), a graphics processing unit (GPU), a neural processing unit (NPU), and a tensor processing unit (TPU), or a combination of two or more, but is not limited to the above examples.

[0189] Referring to Figures 1 to 16 The provided description also applies to Figure 17 the description of , and therefore, for the sake of brevity, the detailed description will be omitted.

[0190] Figure 18 FIG. shows an example electronic device including a battery state estimation device according to one or more embodiments.

[0191] Referring to Figure 18 , in a non-limiting example, the electronic device 1800 may include a battery 110 and a battery state estimation device 120.

[0192] The electronic device 1800 may be applied to a vehicle (e.g., an electric vehicle, etc.), a mobile device (e.g., a smart phone, a tablet personal computer (PC), etc.), etc.

[0193] In one example, the electronic device 1800 may perform the operations of the above-described battery state estimation device 120. The electronic device 1800 may determine a voltage difference between an estimated voltage of the battery 110 determined by a battery model and a sensed voltage of the battery 110 obtained using a voltage sensor. The electronic device 1800 may determine an SOC error amount based on the determined voltage difference. The electronic device 1800 may determine a first cumulative SOC compensation amount, which is a cumulative SOC compensation amount for compensating the SOC of the battery 110 at a partial discharge time point of the battery 110. The electronic device 1800 may estimate a second cumulative SOC compensation amount at a full discharge time point of the battery 110 based on the determined first cumulative SOC compensation amount and a predetermined SOC compensation amount prediction curve. The electronic device 1800 may adjust the estimated second cumulative SOC compensation amount based on the determined SOC error amount. The electronic device 1800 may update an aging parameter of the battery model based on the adjusted second cumulative SOC compensation amount.

[0194] Referring to Figures 1 to 17 The provided description also applies to Figure 18 the description of , and therefore, for the sake of brevity, the detailed description will be omitted.

[0195] Figure 19 FIG. shows an example mobile device according to one or more embodiments.

[0196] Referring toFigure 19 , in a non - limiting example, the mobile device 1900 may include a processor 1910, a memory 1920, a battery 1930, a power management integrated circuit (PMIC) 1940, and a display 1950.

[0197] The memory 1920 may include computer - readable instructions. The processor 1910 may be configured to execute the computer - readable instructions (such as the computer - readable instructions stored in the memory 1920), and by executing the computer - readable instructions, the processor 1910 is configured to perform one or more or any combination of the operations and / or methods described herein. The memory 1920 may be volatile memory or non - volatile memory. The memory 1920 may store a battery model.

[0198] In one example, the PMIC 1940 can charge the battery 1930 with power received from an external device (e.g., a travel adapter or a wireless charger) of the mobile device 1900. The PMIC 1940 can supply the power stored in the battery 1930 to components of the mobile device 1900 (e.g., the processor 1910, etc.).

[0199] The PMIC 1940 can obtain a sensed voltage by sensing the voltage of the battery 1930 through a voltage sensor and transmit the obtained sensed voltage to the processor 1910. In one example, although not shown in Figure 19 , the voltage sensor may be located near the battery 1930, and the voltage sensor can sense the voltage of the battery 1930 and transmit the obtained sensed voltage to the processor 1910.

[0200] The processor 1910 can perform at least some or all of the operations of the above - mentioned battery state estimation device 120.

[0201] In one example, the processor 1910 can control the display 1950 such that the state information (e.g., SOC, etc.) of the battery 1930 is displayed on the display 1950.

[0202] Referring to Figures 1 to 18 The description provided also applies to Figure 19 the description of

[0203] For Figures 1 to 19The described electronic devices, electronic equipment, processors, memories, battery state estimation devices, batteries, battery system 100, battery 110, battery state estimation device 120, battery model 410, compensator 420, voltage sensor 1720, processor 1710, memory 1730, electronic device 1800, mobile device 1900, processor 1910, memory 1920, battery 1930, PMIC 1940, and display 1950 herein described and disclosed are implemented by or represent hardware components. As described above, or in addition to the above description, examples of hardware components that can be used to perform the operations described in this application include, where appropriate: controllers, sensors, generators, drivers, memories, comparators, arithmetic logic units, adders, subtracters, multipliers, dividers, integrators, and any other electronic components configured to perform the operations described in this application. In other examples, one or more of the hardware components that perform the operations described in this application are implemented by computing hardware (e.g., by one or more processors or computers). The processor or computer can be implemented by one or more processing elements (such as, logic gate arrays, controllers and arithmetic logic units, digital signal processors, microcomputers, programmable logic controllers, field programmable gate arrays, programmable logic arrays, microprocessors, or any other device or combination of devices configured to respond and execute instructions in a defined manner to achieve a desired result). In one example, the processor or computer includes or is connected to one or more memories that store instructions or software executed by the processor or computer. The hardware components implemented by the processor or computer can execute instructions or software (such as, an operating system (OS) and one or more software applications running on the OS) to perform the operations described in this application. The hardware components can also access, manipulate, process, create, and store data in response to the execution of the instructions or software. For the sake of brevity, the singular terms "processor" or "computer" may be used in the description of the examples described in this application, but in other examples, multiple processors or computers may be used, or the processor or computer may include multiple processing elements, or multiple types of processing elements, or both. For example, a single hardware component, or two or more hardware components, can be implemented by a single processor, or two or more processors, or a processor and a controller. One or more hardware components can be implemented by one or more processors, or a processor and a controller, and one or more other hardware components can be implemented by one or more other processors, or additional processors and additional controllers. One or more processors, or a processor and a controller, can implement a single hardware component, or two or more hardware components.As described above, or in addition to the above description, example hardware components may have any one or more of different processing configurations. Examples of different processing configurations include: a single processor, a stand-alone processor, a parallel processor, single instruction single data (SISD) multiprocessing, single instruction multiple data (SIMD) multiprocessing, multiple instruction single data (MISD) multiprocessing, and multiple instruction multiple data (MIMD) multiprocessing.

[0204] Figures 1 to 19 The method of performing the operations described in this application, shown in ,

[0204] , and Figures 1 to 19 , is performed by computing hardware (e.g., by one or more processors or computers) that is implemented to execute instructions or software as described above to perform the operations performed by the method described in this application. For example, a single operation, or two or more operations, may be performed by a single processor, or two or more processors, or a processor and a controller. One or more operations may be performed by one or more processors, or a processor and a controller, and one or more other operations may be performed by one or more other processors, or additional processors and additional controllers. One or more processors, or a processor and a controller, may perform a single operation, or two or more operations.

[0205] Instructions or software for controlling computing hardware (e.g., one or more processors or computers) to implement the hardware components and perform the methods described above may be written as a computer program, code segment, instruction, or any combination thereof to individually or jointly direct or configure one or more processors or computers to operate as a machine or special-purpose computer to perform the operations performed by the hardware components and methods described above. In one example, the instructions or software include machine code (such as machine code generated by a compiler) that is directly executed by one or more processors or computers. In another example, the instructions or software include high-level code that is executed by one or more processors or computers using an interpreter. The instructions or software may be written in any programming language based on the block diagrams and flowcharts shown in the figures and the corresponding descriptions herein, which disclose algorithms for performing the operations performed by the hardware components and methods described above.

[0206] Instructions or software for controlling computing hardware (e.g., one or more processors or computers) to implement the hardware components and perform the methods described above, and any associated data, data files, and data structures, can be recorded, stored, or fixed on one or more non-transitory computer-readable storage media, or recorded, stored, or fixed on one or more non-transitory computer-readable storage media, and thus are not signals per se. As described above, or in addition to the above description, examples of non-transitory computer-readable storage media include: read-only memory (ROM), random access programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), flash memory, non-volatile memory, CD-ROM, CD-R, CD+R, CD-RW, CD+RW, DVD-ROM, DVD-R, DVD+R, DVD-RW, DVD+RW, DVD-RAM, BD-ROM, BD-R, BD-R LTH, BD-RE, Blu-ray or optical disc storage devices, hard disk drive (HDD), solid state drive (SSD), flash memory, cartridge memory (such as, multimedia card micro or card (e.g., secure digital (SD) or extreme digital (XD))), magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid state disk, and / or any one or more of any other devices, any other device being configured to store instructions or software and any associated data, data files, and data structures in a non-transitory manner and to provide the instructions or software and any associated data, data files, and data structures to one or more processors or computers such that the one or more processors or computers can execute the instructions. In one example, the instructions or software and any associated data, data files, and data structures are distributed across a networked computer system such that the instructions and software and any associated data, data files, and data structures are stored, accessed, and executed in a distributed manner by one or more processors or computers.

[0207] Although the present disclosure includes specific examples, it will be apparent after understanding the disclosure of this application that various changes in form and detail can be made in these examples without departing from the spirit and scope of the claims and their equivalents. The examples described herein should be considered only as descriptive and not for purposes of limitation. The description of a feature or aspect in each example should be considered applicable to similar features or aspects in other examples. Appropriate results can be achieved if the described techniques are performed in a different order, and / or if the components in the described system, architecture, device, or circuit are combined in a different manner, and / or replaced or supplemented by other components or their equivalents.

[0208] Accordingly, in addition to the above and the disclosure of all the drawings, the scope of the disclosure also includes the claims and their equivalents, that is, all variations within the scope of the claims and their equivalents will be construed as being included in the disclosure.

Claims

1. A method for battery state estimation implemented by a processor, the method comprising: Determining a voltage difference between an estimated voltage of a battery determined by a battery model and a sensed voltage of the battery; Determining a state of charge error amount based on the determined voltage difference; Determining a first cumulative state of charge compensation amount, the first cumulative state of charge compensation amount being a cumulative state of charge compensation amount for compensating the state of charge of the battery at a partial discharge time point of the battery; Estimating a second cumulative state of charge compensation amount at a full discharge time point of the battery based on the determined first cumulative state of charge compensation amount and a predetermined state of charge compensation amount prediction curve; Adjusting the estimated second cumulative state of charge compensation amount based on the determined state of charge error amount; And Updating an aging parameter of the battery model based on the adjusted second cumulative state of charge compensation amount.

2. The method according to claim 1, wherein The step of adjusting the estimated second cumulative state of charge compensation amount includes: Adjusting the estimated second cumulative state of charge compensation amount by subtracting the determined state of charge error amount from the estimated second cumulative state of charge compensation amount or adding the estimated second cumulative state of charge compensation amount to the determined state of charge error amount.

3. The method according to claim 1, wherein The step of determining the voltage difference includes: Determining whether a start condition for determining the state of charge error amount is satisfied; and In response to determining that the start condition is satisfied, determining the voltage difference.

4. The method according to claim 3, wherein, The step of determining whether the start condition is satisfied includes: In response to the anode concentration of the battery reaching a predetermined concentration value or the state of charge of the battery reaching a predetermined state of charge value, determining that the start condition is satisfied.

5. The method according to claim 1, wherein The step of estimating the second cumulative state of charge compensation amount includes: Obtaining a third cumulative state of charge compensation amount corresponding to a partial discharge battery state at the partial discharge time point in a state of charge compensation amount prediction curve; Obtaining a fourth cumulative state of charge compensation amount corresponding to a full discharge battery state at the full discharge time point in the state of charge compensation amount prediction curve; and Using the determined first cumulative state of charge compensation amount, the obtained third cumulative state of charge compensation amount, and the obtained fourth cumulative state of charge compensation amount to estimate the second cumulative state of charge compensation amount.

6. The method according to claim 1, wherein The step of determining the state of charge error amount includes: Obtaining an open circuit voltage corresponding to the state of charge of the battery determined by the battery model in an open circuit voltmeter; and Determining the state of charge error amount by reflecting the determined voltage difference in the obtained open circuit voltage.

7. The method according to claim 1, wherein, The step of determining the state of charge error amount includes: Using the surface concentration of each of a plurality of electrodes of the battery to determine a first open circuit potential of each of the plurality of electrodes; Using each determined first open circuit potential to determine a first open circuit voltage of the battery; Compensating the surface concentration of each electrode based on an initial state of charge error amount; Using each compensated surface concentration to determine a second open circuit potential of each of the plurality of electrodes; Using each determined second open circuit potential to determine a second open circuit voltage of the battery; and Using the determined first open circuit voltage, the determined second open circuit voltage, the initial state of charge error amount, and the determined voltage difference to determine the state of charge error amount.

8. The method according to any one of claims 1 to 7, wherein, The steps of updating the aging parameter include: Storing the aging parameter value calculated based on the adjusted second cumulative state of charge compensation amount in a memory; and Updating the aging parameter by using one or more aging parameter values stored in the memory in response to meeting the update condition of the aging parameter.

9. The method according to any one of claims 1 to 7, wherein, The steps of updating the aging parameter include: Storing the adjusted second cumulative state of charge compensation amount in the memory; Calculating the average value of multiple adjusted second cumulative state of charge compensation amounts stored in the memory in response to meeting the update condition of the aging parameter; and Updating the aging parameter by using the calculated average value.

10. The method according to any one of claims 1 to 7, wherein The aging parameter includes electrode balance offset.

11. A processor-implemented method for battery state estimation, the method including: Determining a state of charge error amount based on a determined voltage difference between an estimated voltage of a battery determined by a battery model and a sensed voltage of the battery; Estimating a second cumulative state of charge compensation amount at a full discharge time point of the battery based on a first cumulative state of charge compensation amount and a predetermined state of charge compensation amount prediction curve, where the first cumulative state of charge compensation amount is a cumulative state of charge compensation amount for compensating the state of charge of the battery at a partial discharge time point of the battery; And Updating an aging parameter of the battery model according to an adjusted estimated second cumulative state of charge compensation amount based on the determined state of charge error amount.

12. An electronic device, including: A processor configured to execute instructions; And A memory storing the instructions and a battery model, where executing the instructions configures the processor to: Determine a voltage difference between an estimated voltage of a battery determined by a battery model and a sensed voltage of the battery; Determine a state of charge error amount based on the determined voltage difference; Determine a first cumulative state of charge compensation amount, where the first cumulative state of charge compensation amount is a cumulative state of charge compensation amount for compensating the state of charge of the battery at a partial discharge time point of the battery; Estimate a second cumulative state of charge compensation amount at a full discharge time point of the battery based on the determined first cumulative state of charge compensation amount and a predetermined state of charge compensation amount prediction curve; Adjust the estimated second cumulative state of charge compensation amount based on the determined state of charge error amount; and Update an aging parameter of the battery model based on the adjusted second cumulative state of charge compensation amount.

13. The electronic device according to claim 12, wherein, The processor is configured to: Adjust the estimated second cumulative state of charge compensation amount by subtracting the determined state of charge error amount from the estimated second cumulative state of charge compensation amount or adding the determined state of charge error amount to the estimated second cumulative state of charge compensation amount.

14. The electronic device according to claim 12, wherein, The processor is configured to: Determine whether a start condition for determining the state of charge error amount is met; and In response to determining that the start condition is met, determine the voltage difference.

15. The electronic device according to claim 14, wherein, The processor is configured to: In response to the anode concentration of the battery reaching a predetermined concentration value or the state of charge of the battery reaching a predetermined state of charge value, determine that the start condition is met.

16. The electronic device according to claim 12, wherein, The processor is configured to: Obtain a third cumulative state of charge compensation amount corresponding to a partial discharge battery state at the partial discharge time point in a state of charge compensation amount prediction curve; Obtain a fourth cumulative state-of-charge compensation amount corresponding to the fully discharged battery state at the fully discharged time point in the state-of-charge compensation amount prediction curve graph; and Estimate the second cumulative state-of-charge compensation amount using the determined first cumulative state-of-charge compensation amount, the obtained third cumulative state-of-charge compensation amount, and the obtained fourth cumulative state-of-charge compensation amount.

17. The electronic device according to claim 12, wherein, The processor is configured to: Obtain an open-circuit voltage corresponding to the state-of-charge of the battery determined by the battery model in the open-circuit voltage meter; and Determine a state-of-charge error amount by reflecting the determined voltage difference in the obtained open-circuit voltage.

18. The electronic device according to claim 12, wherein, The processor is configured to: Use the surface concentration of each of the plurality of electrodes of the battery to determine a first open-circuit potential of each of the plurality of electrodes; Use each determined first open-circuit potential to determine a first open-circuit voltage of the battery; Compensate each determined surface concentration based on the initial state-of-charge error amount; Use each compensated surface concentration to determine a second open-circuit potential of each of the plurality of electrodes; Use each determined second open-circuit potential to determine a second open-circuit voltage of the battery; And Use the determined first open-circuit voltage, the determined second open-circuit voltage, the initial state-of-charge error amount, and the determined voltage difference to determine a state-of-charge error amount.

19. The electronic device according to any one of claims 12 to 18, wherein, The processor is configured to: Store the aging parameter value calculated based on the adjusted second cumulative state-of-charge compensation amount in the memory; and In response to satisfying the update condition of the aging parameter, update the aging parameter using one or more aging parameter values stored in the memory.

20. The electronic device according to any one of claims 12 to 18, wherein, The processor is configured to: Store the adjusted second cumulative state-of-charge compensation amount in the memory; In response to satisfying the update condition of the aging parameter, calculate the average value of the plurality of adjusted second cumulative state-of-charge compensation amounts stored in the memory; And Use the calculated average value to update the aging parameter.

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