Battery management device, battery management method, and battery management system

Abstract

According to some embodiments disclosed in the present document, a battery management device comprises a sensor configured to collect battery data from a battery to be managed and a controller configured to: extract, from the battery data, a data set relating to charging and discharging speed and voltage for each of multiple reference SOC values; generate a first profile of the voltage according to a charging and discharging speed by performing fitting on the data set at each reference SOC value; on the basis of the first profile at each reference SOC value, generate a second profile of the voltage according to the SOC for each of multiple charging and discharging speeds; and estimate a state of the battery to be managed on the basis of multiple second profiles corresponding to the multiple charging and discharging speeds.

Description

Battery management device, battery management method, and battery management system

[0001] Cross-citation with related applications

[0002] This application claims the benefit of priority to Republic of Korea Patent Application No. 10-2023-0160215, filed November 20, 2023, the entire contents of which are incorporated herein by reference.

[0003] Technology field

[0004] Embodiments disclosed in this document relate to a battery management device, a battery management method, and a battery management system.

[0005] Recently, active research and development has been conducted on secondary batteries. The term "secondary battery" refers to a rechargeable battery, encompassing both conventional Ni / Cd and Ni / MH batteries, as well as recent lithium-ion batteries. Among secondary batteries, lithium-ion batteries can boast higher energy densities than conventional Ni / Cd and Ni / MH batteries. They can be manufactured in small and lightweight designs, making them highly versatile power sources for mobile devices. Recently, their use has expanded to include power sources for electric vehicles, attracting attention as a next-generation energy storage medium.

[0006] Battery data such as voltage, current, temperature, and SOC can be analyzed to estimate the condition of batteries used in vehicles and other applications. For example, battery conditions such as resistance degradation can be diagnosed. To do this, mixed battery data for multiple charge / discharge rates (c-rates) can be separated into individual charge / discharge rates. Meanwhile, the performance of the condition diagnosis can vary depending on how the data is fitted during the charge / discharge rate separation process.

[0007] One purpose of the embodiments disclosed in this document is to provide a battery management device, a battery management method, and a battery management system capable of improving a data fitting method in the process of separating battery data for each charge / discharge rate to improve the performance of state diagnosis.

[0008] The technical objectives of the embodiments disclosed in this document are not limited to the technical tasks mentioned above, and other technical tasks not mentioned will be clearly understood by those skilled in the art from the descriptions below.

[0009] According to some embodiments disclosed in the present document, a battery management device includes a sensor configured to collect battery data from a battery to be managed; and a controller configured to extract a dataset relating to charge / discharge rates and voltages for each of a plurality of reference SOC values ​​from the battery data, perform a fitting on the dataset at each reference SOC value to generate a first profile of voltage according to charge / discharge rates, generate a second profile of voltage according to SOC for each of a plurality of charge / discharge rates based on the first profile at each reference SOC value, and estimate a state of the battery to be managed based on the plurality of second profiles corresponding to the plurality of charge / discharge rates.

[0010] In some embodiments, the controller is configured to generate the first profile by performing an optimized polynomial fitting for the dataset at each reference SOC value.

[0011] In some embodiments, the controller is configured to determine a most suitable polynomial degree for the dataset, and to generate the first profile by minimizing a difference between the estimated polynomial according to the polynomial degree and the dataset.

[0012] According to some embodiments, the controller is further configured to generate a third profile of resistance of the managed battery according to SOC based on the plurality of second profiles, and to estimate a resistance degradation state of the managed battery based on the third profile.

[0013] In some embodiments, the controller is configured to estimate the resistance degradation state by comparing the third profile with the resistance profile at the time of manufacture of the managed battery.

[0014] According to some embodiments, the controller is configured to perform current accumulation and Kalman filter error correction on the battery data to generate correction data, and to extract the dataset based on the correction data.

[0015] In some embodiments, the sensor is configured to collect battery data from the managed battery that is charged or discharged by a power-using device including the managed battery.

[0016] According to some embodiments disclosed in the present document, a battery management method includes the steps of collecting battery data from a battery to be managed; extracting a dataset regarding charge / discharge rates and voltage for each of a plurality of reference SOC values ​​from the battery data; performing a fitting on the dataset at each reference SOC value to generate a first profile of voltage according to charge / discharge rates; generating a second profile of voltage according to SOC for each of a plurality of charge / discharge rates based on the first profile at each reference SOC value; and estimating a state of the battery to be managed based on the plurality of second profiles corresponding to the plurality of charge / discharge rates.

[0017] In some embodiments, the step of generating the first profile comprises the step of generating the first profile by performing an optimal polynomial fit for the dataset at each reference SOC value.

[0018] In some embodiments, the step of generating the first profile comprises: determining a polynomial degree most suitable for the dataset; and generating the first profile by minimizing a difference between the estimated polynomial according to the polynomial degree and the dataset.

[0019] In some embodiments, the battery management method further comprises: generating a third profile of the resistance of the managed battery according to the SOC based on the plurality of second profiles; and estimating a resistance degradation state of the managed battery based on the third profile.

[0020] In some embodiments, the step of estimating the resistance degradation state includes the step of estimating the resistance degradation state by comparing the third profile with the resistance profile at the time of manufacturing of the battery to be managed.

[0021] In some embodiments, the step of extracting the dataset includes the step of performing current integration and Kalman filter error correction on the battery data to generate correction data; and the step of extracting the dataset based on the correction data.

[0022] According to some embodiments, the step of collecting the battery data comprises the step of collecting the battery data from the managed battery that is charged or discharged by a power usage device including the managed battery.

[0023] According to some embodiments disclosed in the present document, a battery management system includes a managed battery that is charged or discharged by a power usage device; and a battery management device configured to collect battery data from the managed battery, extract a dataset regarding charge / discharge rates and voltages for each of a plurality of reference SOC values ​​from the battery data, perform fitting on the dataset at each reference SOC value to generate a first profile of voltage according to charge / discharge rates, generate a second profile of voltage according to SOC for each of a plurality of charge / discharge rates based on the first profile at each reference SOC value, and estimate a state of the managed battery based on the plurality of second profiles corresponding to the plurality of charge / discharge rates.

[0024] According to the embodiments disclosed in this document, a battery management device, a battery management method, and a battery management system can be provided that can improve the data fitting method in the process of separating battery data for each charge / discharge rate to improve the performance of status diagnosis.

[0025] The technical effects according to the embodiments disclosed in this document are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art according to the disclosure of this document.

[0026] FIG. 1 may illustrate elements constituting a battery management system according to some embodiments.

[0027] FIG. 2 may illustrate elements constituting a battery management device according to some embodiments.

[0028] FIG. 3 can illustrate a process of generating accumulated data of voltage according to SOC by measuring battery data according to some embodiments.

[0029] FIG. 4 may illustrate SOC and voltage of battery data according to some embodiments.

[0030] FIGS. 5 to 7 illustrate a first profile through a dataset and data fitting thereof at each reference SOC value according to some embodiments.

[0031] FIG. 8 may illustrate a second profile for each of a plurality of charge / discharge rates according to some embodiments.

[0032] FIG. 9 may illustrate a third profile of battery resistance according to SOC according to some embodiments.

[0033] FIG. 10 may illustrate steps of a battery management method according to some embodiments.

[0034] Hereinafter, embodiments described in this document are described with reference to the attached drawings. However, this is not intended to limit the disclosure of this document to specific embodiments, and it should be understood that various modifications, equivalents, and / or alternatives of the embodiments described in this document are included.

[0035] The embodiments and terminology used in this document are not intended to limit the technical features described in this document to a specific embodiment, but should be understood to encompass various modifications, equivalents, or alternatives of the embodiment. In connection with the description of the drawings, similar reference numerals may be used to refer to similar or related components. The singular form of a noun corresponding to an item may include one or more of the item, unless the context clearly indicates otherwise.

[0036] In this document, the phrases "A or B", "at least one of A and B", "at least one of A or B", "A, B, or C", "at least one of A, B, and C", and "at least one of A, B, or C" can each include any one of the items listed together in that phrase, or all possible combinations thereof. Terms such as "first", "second", "first", "second", "A", "B", "(a)", or "(b)" may be used merely to distinguish the corresponding component from other corresponding components, and do not limit the corresponding components in any other respect (e.g., importance or order) unless specifically stated otherwise.

[0037] In this document, when a component (e.g., a first component) is referred to as being “connected,” “coupled,” or “connected,” with or without the terms “functionally” or “communicatively,” or “coupled” or “connected,” it means that the component can be connected to the other component directly (e.g., wired or wirelessly), or indirectly (e.g., via a third component).

[0038] The methods according to various embodiments disclosed in this document may be provided as a computer program product. The computer program product may be traded as a commodity between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read-only memory, CD-ROM), or may be distributed online (e.g., downloaded or uploaded) through an application store or directly between two driver devices. In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0039] According to the embodiments disclosed in this document, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separated and placed in other components. According to the embodiments disclosed in this document, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to the embodiments disclosed in this document, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0040] FIG. 1 may illustrate elements constituting a battery management system according to some embodiments.

[0041] Referring to FIG. 1, a battery management system (100) may include a power usage device (110), a managed battery (120), a battery management device (130), and a management server (140). However, the present invention is not limited thereto, and some components may be omitted from the battery management system (100) or other general-purpose components may be further included in the battery management system (100).

[0042] A battery management system (100) may refer to a system for diagnosing a managed battery (120) and managing its status. When a managed battery (120) is charged or discharged by a power usage device (110), battery data of the managed battery (120) resulting from the charge or discharge can be measured and analyzed by a battery management device (130).

[0043] The power usage device (110) may be configured to charge or discharge the managed battery (120). The power usage device (110) may discharge the managed battery (120) while consuming power, and may charge the managed battery (120) while generating power. According to an embodiment, the power usage device (110) may include a mobility device such as an electric vehicle or an electric bike. The mobility device may drive a motor based on the power of the managed battery (120) or charge the managed battery (120) with power generated through regenerative braking.

[0044] The battery to be managed (120) may include a battery pack or the like that is to be managed by the battery management system (100). The battery pack of the battery to be managed (120) may include a plurality of battery modules, and each battery module may include a plurality of battery cells. According to an embodiment, the battery to be managed (120) may be mounted on a mobility device such as an electric vehicle or an electric bike.

[0045] The battery management device (130) can perform operations for diagnosing or managing the managed battery (120). The battery management device (130) can measure battery data from the managed battery (120) and diagnose or manage the status of the managed battery (120) based on the measured battery data.

[0046] The management server (140) can manage the diagnostic results of the battery management device (130). The management server (140) can exchange data with the battery management device (130) via wired / wireless communication. When a defect in the managed battery (120) is diagnosed or its lifespan is predicted, the results can be transmitted to the management server (140) and recorded in a database.

[0047] According to an embodiment, the management server (140) may perform operations for managing a managed battery (120) on behalf of the battery management device (130). According to an embodiment, the battery management device (130) may perform diagnostic operations by executing battery management software, and the management server (140) may provide update information of the battery management software to the battery management device (130).

[0048] FIG. 2 may illustrate elements constituting a battery management device according to some embodiments.

[0049] Referring to FIG. 2, the battery management device (130) may include a sensor (131) and a controller (132). However, the present invention is not limited thereto, and some components may be omitted from the battery management device (130), or other general-purpose components may be further included in the battery management device (130).

[0050] According to an embodiment, the sensor (131) and the controller (132) in the battery management device (130) may be electrically connected to each other through a device-to-device communication method. The device-to-device communication method may include a bus, a general purpose input and output (GPIO), a serial peripheral interface (SPI), a mobile industry processor interface (MIPI), etc.

[0051] The sensor (131) may be configured to generate various battery measurements from the battery to be managed (120). To this end, the sensor (131) may include measuring means such as a voltage sensor, a current sensor, and a temperature sensor.

[0052] The controller (132) may have a structure for executing commands that implement the operations of the battery management device (130). The controller (132) may be implemented as an array of multiple logic gates for processing various operations or as a general-purpose microprocessor, and may be composed of a single processor or multiple processors. For example, the controller (132) may be implemented in the form of at least one of a microprocessor, a CPU, a GPU, and an AP.

[0053] The controller (132) can operate with a memory configured to store various data, commands, mobile applications, computer programs, etc. The memory can be configured separately from or integrally with the controller (132). The controller (132) can process various operations by executing commands stored in the memory. For example, the memory can be implemented as a non-volatile device such as a ROM, a PROM, an EPROM, an EEPROM, a flash memory, a PRAM, an MRAM, an RRAM, an FRAM, etc., or a volatile device such as a DRAM, an SRAM, an SDRAM, a PRAM, etc., and can be implemented in the form of an HDD, an SSD, an SD, a Micro-SD, etc., or a combination thereof.

[0054] The sensor (131) may be configured to collect battery data from the managed battery (120). The battery data may include voltage, current, temperature, etc. of the managed battery (120) measured at regular intervals. According to an embodiment, the state of charge (SOC) of the managed battery (120) may be derived based on the voltage, current, temperature, etc. of the battery data, and the charge / discharge state (CR, c-rate) of the managed battery (120) may be derived based on the current, etc. of the battery data. When the charge / discharge state is 0, the managed battery (120) may be in an open circuit state, and the voltage at that time may be an open circuit voltage (OCV). The sign (+ / -) of the charge / discharge state may indicate whether the managed battery (120) is in a charged state or a discharged state.

[0055] The controller (132) obtains a plurality of reference SOC values ​​(SOC1-SOC) from the battery data. n ) for each of the data sets on charge / discharge rate (CR, c-rate) and voltage (S i) can be configured to extract. For this, reference may be made to FIGS. 3 to 7, which will be described later. Battery data may include a plurality of measurement values ​​generated for each measurement period, and the measurement values ​​at each point in time may include voltage values, current values, and temperature values, and the SOC value at each point in time may be additionally derived. According to an embodiment, a graph (330) that plots data representing the SOC value and voltage value at each point in time may be generated, and based on this, a dataset (S i ) can be extracted. For example, reference SOC values ​​(SOC x , SOC y , SOC z ) and extract the corresponding SOC-voltage data for each dataset (S x , S y , S z ) can be created.

[0056] The controller (132) determines each reference SOC value (SOC i ) in the dataset (S i ) to perform fitting for the first profile (P1) of voltage according to the charge / discharge rate (CR). i ) can be configured to generate a specific SOC value (SOC) from the accumulated data of SOC-voltage measured at multiple points in time, such as the graph (330). x ) to extract measurements and create a dataset (S x ) can be generated. Dataset (S x ) can have charge / discharge rate (CR) and voltage (V) as in the graph (500), and the data set (S x ) best fitting the pattern of the first profile (P1) x ) can be derived. For example, the first profile (P1 x ) can be expressed as a first-degree polynomial.

[0057] The controller (132) determines each reference SOC value (SOC i ) in the first profile (P1) i) based on the second profile of voltage according to SOC (P2) j ) with multiple charge / discharge speeds (CR1-CR m ) can be configured to generate for each of the second profiles (P2 j ) can be referred to in the following Fig. 8. For example, the reference SOC value (S) of the graph (700) z ) to the graph (800) using multiple reference SOC values ​​(S1-S 1n ) for multiple charge / discharge rates (CR1-CR m ) for the second profiles (P21-P2) m ) can be created.

[0058] The controller (132) has multiple charge / discharge speeds (CR1-CR m ) corresponding to a plurality of second profiles (P21-P2) m ) can be configured to estimate the state of the managed battery (120) based on a plurality of second profiles (P21-P2 m ) of the managed battery (120) can be diagnosed based on the resistance degradation (SOHR), and the life of the managed battery (120) can be estimated based on the value of the resistance degradation (SOHR). For example, a specific SOC value (SOC) of the graph (800) z ) for multiple charge / discharge rates (CR1-CR m ) and multiple voltage values ​​can be provided, so that a specific SOC value (SOC z ) can be estimated for the resistance value of the battery (120) to be managed.

[0059] According to the embodiment, the controller (132) determines each reference SOC value (SOC i ) in the dataset (S i ) to perform optimized polynomial fitting for the first profile (P1 i) can be configured to generate a dataset (S) of a graph (500). For example, x ) is a first-degree polynomial (P1 x ) is fitted, whereas the dataset (S) of the graph (600) y ) is a second-degree polynomial (P1 y ) can be fitted. Dataset (S i ) can be fitted with a polynomial that best suits the pattern, the accuracy of data fitting and the performance of condition diagnosis can be improved compared to when fitting uniformly with a linear or quadratic equation.

[0060] According to an embodiment, the controller (132) comprises a dataset (S i ) to determine the most appropriate polynomial degree, and a dataset (S) of estimated polynomials according to the polynomial degree. i ) to minimize the difference with the first profile (P1) i ) can be configured to generate. For this purpose, various curve fitting models can be utilized, and after the polynomial degree is determined, the coefficients of the estimated polynomial can be adjusted using the least squares method, etc.

[0061] According to an embodiment, the controller (132) comprises a plurality of second profiles (P21-P2 m ) can be further configured to generate a third profile (P3) of the resistance of the managed battery (120) according to the SOC, and estimate the resistance degradation state of the managed battery (120) based on the third profile (P3). For example, each reference SOC value (SOC i ) at multiple charge / discharge rates (CR1-CR m ) and multiple voltage values ​​to determine resistance degradation (SOHR) i ) can be estimated, and this process is based on the reference SOC values ​​(SOC1-SOC n ) can be repeatedly generated for the third profile (P3) of SOHR according to SOC.

[0062] According to an embodiment, the controller (132) may be configured to estimate a resistance degradation state by comparing the third profile (P3) with the resistance profile at the time of manufacturing of the managed battery (120). For example, as shown in the graph (900) of FIG. 9 described below, as the degradation of the managed battery (120) progresses, the resistance of the managed battery (120) may increase, and thus the resistance degradation state may be estimated by comparing this with a reference time point.

[0063] According to an embodiment, the controller (132) performs current accumulation and Kalman filter error correction on battery data to generate correction data, and generates a dataset (S) based on the correction data. i ) can be configured to extract current values. Current accumulation may include a method of processing battery data by accumulating current values, through which SOC-voltage data can be generated. If error correction is performed through a Kalman filter, a data plot such as the graph (330) can be formed.

[0064] According to an embodiment, the sensor (131) may be configured to collect battery data from a managed battery (120) that is charged or discharged by a power-using device including the managed battery (120). For example, the power-using device may include an electric vehicle, and while the managed battery (120) is charged or discharged by a motor of the electric vehicle, voltage, current, temperature, etc. may be measured at each point in time at regular intervals.

[0065] FIG. 3 can illustrate a process of generating accumulated data of voltage according to SOC by measuring battery data according to some embodiments.

[0066] Referring to FIG. 3, a process of measuring battery data (310) from a managed battery (120) and generating a graph (330) of accumulated data of voltage according to SOC may be illustrated. The graph (330) of accumulated data may include a plurality of SOC-voltage matching values.

[0067] According to an embodiment, SOC data (320) can be derived from battery data (310) by current integration or other suitable method. Here, error correction using a Kalman filter or the like can be performed as needed. Both battery data (310) and SOC data (320) can include multiple data measured at multiple points in time. By setting the SOC value and voltage value in the SOC data (320) as a single point and plotting the multiple points in two dimensions, a graph (330) of accumulated data can be generated.

[0068] FIG. 4 may illustrate SOC and voltage of battery data according to some embodiments.

[0069] Referring to FIG. 4, a graph (330) that accumulates and displays data points of SOC and voltage derived from battery data may be illustrated. The graph (330) may be configured to display a plurality of charge / discharge rates (CR1-CR m ) can be displayed without distinction between the SOC-voltage matching values ​​measured for each.

[0070] Graph (330) shows SOC-voltage matching values ​​at multiple charge / discharge rates (CR1-CR m ) are displayed without distinction, a processing step may be required to distinguish them. For example, the reference SOC values ​​(S x , S y , S z Data points for the charge / discharge rates (CR1-CR) can be extracted, and the extracted points can be processed from different perspectives to obtain multiple charge / discharge rates (CR1-CR). m) may be distinguished. Once the distinction is completed, a plurality of data points of the graph (330) may be distinguished from a plurality of second profiles (P21-P2) of the graph (900). m ) can be separated.

[0071] FIGS. 5 to 7 illustrate a first profile through a dataset and data fitting thereof at each reference SOC value according to some embodiments.

[0072] Referring to Figures 5 to 7, some datasets (S x , S y , S z ) can be shown graphs (500, 600, 700) illustrating the optimal polynomial fit for each dataset (S i ) may include matching values ​​of charge / discharge rate (CR) and voltage, and the number of data may vary depending on the vehicle's driving pattern or battery usage time.

[0073] Each dataset (S i ) according to the data distribution pattern of each dataset (S i ) can be fitted with a polynomial of the most appropriate degree. For example, the dataset (S) of the graph (500) x ) can be fitted with a first-order polynomial, while the dataset (S) of the graph (600) y ) can be fitted with a second-order polynomial. In this way, the performance of data fitting and the accuracy of status diagnosis can be improved because the fitting order of various patterns may not be fixed. Each dataset (S i ) When data fitting is completed through optimal polynomial fitting, the voltage value at the charge / discharge rate (CR) value for which no measurement point exists can be estimated.

[0074] FIG. 8 may illustrate a second profile for each of a plurality of charge / discharge rates according to some embodiments.

[0075] Referring to Figure 8, multiple charge / discharge speeds (CR1-CR m ) for each of the second profiles (P2) j ) can be shown. The graph (800) represents the data points of the graph (330) at multiple charge / discharge rates (CR1-CR m ) can be displayed separately.

[0076] Second Profile (P2) j ) is a specific charge / discharge rate (CR) j ) can be generated by collecting voltage values ​​at each SOC value. For example, in the graph (700), some SOC values ​​(SOC z ) can be displayed on the graph (800), and repeating this method for other SOC values ​​produces a second profile (P2 j ) can be formed.

[0077] The graph (800) may include second profiles (P21-P27) for 0 CR, ±1 CR, ±2 CR, and ±3 CR. On the other hand, in cases where there is no direct measurement point, such as 0.5 CR or 1.5 CR, the corresponding value may be included in the first profile (P1) in the graph (500) to the graph (700). i ) can be estimated from the polynomial.

[0078] FIG. 9 may illustrate a third profile of battery resistance according to SOC according to some embodiments.

[0079] Referring to FIG. 9, a graph (900) representing a third profile (P3) of battery resistance according to SOC can be illustrated.

[0080] In the graph (900), the third profile (P3) can be generated by collecting resistance values ​​at each SOC value. For example, a plurality of charge / discharge rate (CR) values ​​and voltage values ​​can be provided at each SOC value in the graph (800), and since the charge / discharge rate (CR) values ​​can correspond to current values, the resistance value at each SOC value can be estimated based on the pattern of these values.

[0081] The third profile (P3) can be compared with the reference resistance profile (910), through which the resistance degradation state of the battery (120) to be managed can be estimated. According to an embodiment, the reference resistance profile (910) can mean the resistance by SOC measured at the beginning of life (BOL) state of the battery to be managed (120). The greater the resistance difference (ΔR) between the third profile (P3) and the reference resistance profile (910), the more severe the resistance degradation of the battery to be managed (120) can be determined to be.

[0082] FIG. 10 may illustrate steps of a battery management method according to some embodiments.

[0083] Referring to FIG. 10, the battery management method (1000) may include steps (1010) to (1050). However, the present invention is not limited thereto, and some steps may be omitted or other general steps may be added, and the steps of the battery management method (1000) may be executed in a different order than the illustrated order.

[0084] The battery management method (1000) may be composed of steps that are processed in a time-series manner in the battery management device (130). Therefore, even if the details are omitted below, the details described above for the battery management device (130) may be equally applied to the battery management method (1000).

[0085] Steps (1010) to (1050) of the battery management method (1000) can be performed by the sensor (131) and controller (132) of the battery management device (130).

[0086] In step (1010), the battery management device (130) can collect battery data from the battery to be managed.

[0087] In step (1020), the battery management device (130) obtains a plurality of reference SOC values ​​(SOC1-SOC) from the battery data. n ) for each of the data sets on charge / discharge rate (CR, c-rate) and voltage (S i ) can be extracted.

[0088] In step (1030), the battery management device (130) calculates each reference SOC value (SOC i ) in the dataset (S i ) to perform fitting for the first profile (P1) of voltage according to the charge / discharge rate (CR). i ) can be created.

[0089] In step (1040), the battery management device (130) calculates each reference SOC value (SOC i ) in the first profile (P1) i ) based on the second profile of voltage according to SOC (P2) j ) with multiple charge / discharge speeds (CR1-CR m ) can be generated for each.

[0090] In step (1050), the battery management device (130) sets a plurality of charge / discharge speeds (CR1-CR m ) corresponding to a plurality of second profiles (P21-P2) m ) can be used to estimate the status of the battery to be managed.

[0091] According to an embodiment, the battery management method (1000) may be implemented in the form of a computer program stored on a computer-readable storage medium. That is, the computer program may include instructions for implementing the battery management method (1000), and the program instructions may be stored on the computer-readable storage medium. The computer program may include a mobile application.

[0092] According to an embodiment, the computer-readable storage medium may include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs, DVDs, magneto-optical media such as floptical disks, and hardware devices specially configured to store and execute computer program instructions such as ROMs, RAMs, flash memories, and the like. The computer program instructions may include machine language codes generated by a compiler and high-level language codes that can be executed by a computer using an interpreter, etc.

[0093] The terms "include," "comprise," or "have" used herein, unless otherwise specifically stated, imply that the corresponding component may be included, and therefore should be interpreted to include other components rather than to exclude other components. All terms, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which the embodiments disclosed in this document pertain, unless otherwise defined. Commonly used terms, such as terms defined in dictionaries, should be interpreted to be consistent with their contextual meaning in the relevant art, and shall not be interpreted in an idealized or overly formal sense, unless explicitly defined in this document.

[0094] The above description is merely an illustrative description of the technical idea disclosed in this document, and those skilled in the art to which the embodiments disclosed in this document pertain may make various modifications and variations without departing from the essential characteristics of the embodiments disclosed in this document. Therefore, the embodiments disclosed in this document are not intended to limit the technical idea of ​​the embodiments disclosed in this document, but to explain it, and the scope of the technical idea disclosed in this document is not limited by these embodiments. The protection scope of the technical idea disclosed in this document should be interpreted by the claims below, and all technical ideas within a scope equivalent thereto should be interpreted as being included in the scope of rights of this document.

[0095] [Explanation of symbols]

[0096] 100: Battery management system 110: Power usage device

[0097] 120: Battery to be managed 130: Battery management device

[0098] 131: Sensor 132: Controller

[0099] 140: Management Server

Claims

1. A sensor configured to collect battery data from a battery to be managed; and Extract a data set on charge / discharge speed and voltage for each of multiple reference SOC values ​​from the above battery data, A first profile of voltage according to charge / discharge rate is generated by performing a fitting on the above dataset at each reference SOC value, Based on the first profile at each reference SOC value, a second profile of voltage according to SOC is generated for each of a plurality of charge / discharge rates, A battery management device comprising a controller configured to estimate a state of the managed battery based on a plurality of second profiles corresponding to the plurality of charge / discharge speeds.

2. In paragraph 1, A battery management device, wherein the controller is configured to generate the first profile by performing optimized polynomial fitting for the dataset at each reference SOC value.

3. In paragraph 2, The above controller determines the most suitable polynomial degree for the above dataset, A battery management device configured to generate the first profile by minimizing the difference between the estimated polynomial according to the polynomial degree and the dataset.

4. In paragraph 1, The controller generates a third profile of the resistance of the managed battery according to the SOC based on the plurality of second profiles, A battery management device further configured to estimate a resistance degradation state of the managed battery based on the third profile.

5. In paragraph 4, A battery management device, wherein the controller is configured to estimate the resistance degradation state by comparing the third profile with the resistance profile at the time of manufacturing of the battery to be managed.

6. In paragraph 1, The above controller generates correction data by performing current accumulation and Kalman filter error correction on the battery data, A battery management device configured to extract the dataset based on the above correction data.

7. In paragraph 1, A battery management device, wherein the sensor is configured to collect battery data from the managed battery that is charged or discharged by a power usage device including the managed battery.

8. Step of collecting battery data from the managed battery; A step of extracting a data set regarding charge / discharge speed and voltage for each of a plurality of reference SOC values ​​from the above battery data; A step of generating a first profile of voltage according to charge / discharge rate by performing fitting on the above dataset at each reference SOC value; A step of generating a second profile of voltage according to SOC for each of a plurality of charge / discharge rates based on the first profile at each reference SOC value; and A battery management method, comprising a step of estimating a state of the managed battery based on a plurality of second profiles corresponding to the plurality of charge / discharge speeds.

9. In paragraph 8, The step of generating the first profile is: A battery management method, comprising the step of generating the first profile by performing an optimal polynomial fitting for the dataset at each reference SOC value.

10. In paragraph 9, The step of generating the first profile is: A step of determining the most suitable polynomial degree for the above dataset; and A battery management method, comprising the step of generating the first profile by minimizing the difference between the estimated polynomial according to the polynomial degree and the dataset.

11. In paragraph 8, A step of generating a third profile of the resistance of the battery to be managed according to the SOC based on the plurality of second profiles; and A battery management method further comprising a step of estimating a resistance degradation state of the managed battery based on the third profile.

12. In paragraph 11, The step of estimating the above resistance degradation state is: A battery management method, comprising a step of estimating the resistance degradation state by comparing the third profile with the resistance profile at the time of manufacturing the battery to be managed.

13. In paragraph 8, The steps for extracting the above dataset are: A step of generating correction data by performing current integration and Kalman filter error correction on the above battery data; and A battery management method, comprising a step of extracting the dataset based on the correction data.

14. In paragraph 8, The steps for collecting the above battery data are: A battery management method, comprising the step of collecting battery data from the managed battery that is charged or discharged by a power usage device including the managed battery.

15. A managed battery that is charged or discharged by a power-using device; and A battery management system comprising a battery management device configured to collect battery data from the managed battery, extract a dataset regarding charge / discharge rates and voltage for each of a plurality of reference SOC values ​​from the battery data, perform fitting on the dataset at each reference SOC value to generate a first profile of voltage according to charge / discharge rates, generate a second profile of voltage according to SOC for each of a plurality of charge / discharge rates based on the first profile at each reference SOC value, and estimate a state of the managed battery based on the plurality of second profiles corresponding to the plurality of charge / discharge rates.

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