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WO2025100624A1 - Programme de diagnostic de batterie utilisant une résistance interne de batterie stockée dans un support d'enregistrement - Google Patents

Programme de diagnostic de batterie utilisant une résistance interne de batterie stockée dans un support d'enregistrement Download PDF

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Publication number
WO2025100624A1
WO2025100624A1 PCT/KR2023/019892 KR2023019892W WO2025100624A1 WO 2025100624 A1 WO2025100624 A1 WO 2025100624A1 KR 2023019892 W KR2023019892 W KR 2023019892W WO 2025100624 A1 WO2025100624 A1 WO 2025100624A1
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WIPO (PCT)
Prior art keywords
battery
internal resistance
heat generation
recording medium
data
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Pending
Application number
PCT/KR2023/019892
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English (en)
Korean (ko)
Inventor
김상범
김영준
김성현
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Btr Co Ltd
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Btr Co Ltd
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Publication of WO2025100624A1 publication Critical patent/WO2025100624A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
    • G01R19/02—Measuring effective values, i.e. root-mean-square values
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R27/00—Arrangements for measuring resistance, reactance, impedance, or electric characteristics derived therefrom
    • G01R27/02—Measuring real or complex resistance, reactance, impedance, or other two-pole characteristics derived therefrom, e.g. time constant
    • G01R27/08—Measuring resistance by measuring both voltage and current
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/389—Measuring internal impedance, internal conductance or related variables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
    • H01M10/486—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte for measuring temperature
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries

Definitions

  • the present invention relates to a battery diagnosis program using the internal resistance of a battery stored in a recording medium, and more specifically, to a battery diagnosis program using the internal resistance of a battery stored in a recording medium, which can predict battery deterioration and diagnose the internal health of a battery by analyzing the change in the internal resistance of the battery according to the temperature change of the battery and the state of charge (SoC) of the battery based on the charge/discharge rate (C-rate) of the battery to be diagnosed.
  • SoC state of charge
  • Batteries also known as accumulators or secondary batteries, have electrical characteristics such as high energy density, and are attracting attention as a new energy source for environmental friendliness and energy efficiency enhancement, as they not only have the primary advantage of reducing the use of fossil fuels but also do not produce any by-products from energy use.
  • batteries are being widely used in portable devices, electric vehicles (EVs) driven by electric power sources, and energy storage systems (ESSs), and research and development on battery management systems (BMSs), battery balancing circuits, and relay circuits are being actively conducted for more efficient battery management.
  • EVs electric vehicles
  • ESSs energy storage systems
  • BMSs battery management systems
  • BMS is becoming a key technology for stable system operation by monitoring the battery's remaining capacity (State Of Charging; SOC), remaining life (State Of Health; SOH), maximum input/output power allowance, output voltage, etc. using the battery's status information.
  • BMS Battery Management System
  • secondary batteries are generally expensive and these replacement secondary batteries often have electrical energy storage capabilities that are suitable for other applications, even if they are not suitable for the original use of electric vehicles.
  • the internal health (State Of Health) of the battery must be identified to diagnose its remaining lifespan.
  • the voltage of the battery cell, the current in the charge/discharge state, and the temperature were measured and monitored to diagnose the battery lifespan.
  • the present invention has been made to solve the above-described problems, and the purpose of the present invention is to diagnose the internal health of a battery without being affected by the battery operating state (charge/discharge, stop, standby state), and to improve the accuracy of battery state diagnosis by calculating and analyzing data necessary for diagnosing the life of the battery based on the measured voltage, current, and temperature of the battery.
  • a battery diagnosis program using the internal resistance of a battery stored in a recording medium characterized in that the computer functions as: a data collection means for collecting data measuring voltage, current and temperature of a battery cell to be diagnosed; a battery internal resistance calculation means for calculating the internal resistance of the battery using the voltage and current data measured from the battery cell; a battery heat generation prediction means for deriving a temperature change during charging and discharging of the battery using the temperature data measured from the battery cell and predicting the heat generation of the battery; a battery deterioration prediction means for predicting the deterioration of the battery based on the internal resistance data calculated from the battery internal resistance calculation means and the battery heat generation prediction data derived from the battery heat generation prediction means; and a battery state diagnosis means for diagnosing the internal health (State of Health, SOH) of the battery indicating the degree of aging and remaining life of the battery based on the result data derived from the battery deterioration prediction means.
  • SOH Sty health
  • the battery internal resistance calculation means calculates the sum of the Ohmic resistance, the charge transfer resistance and the diffusion resistance measured from the battery cell as the internal resistance value of the battery.
  • the battery internal resistance calculation means precisely calculates the battery internal resistance by using the root mean square values of voltage change values and current change values of the battery cell measured in the battery when an AC signal periodically generates a signal change by continuously turning ON/OFF a switch of the battery.
  • the battery internal resistance calculation means repeatedly classifies the calculated battery internal resistance data through database statistics to correct the error range in order to improve the accuracy of the calculated data.
  • the heat generation prediction means predicts the battery heat generation using a battery heat generation model generated by learning the correlation between the anisotropic heat transfer properties of jelly rolls of various batteries and the electrical and thermal characteristics of the battery cell itself and the temperature change data during charge and discharge of the battery.
  • the heat generation prediction means predicts the battery heat generation by calculating the sum of the reversible heat generation and the irreversible heat generation of the battery cell.
  • the deterioration prediction means measures the charge/discharge rate (C-rate) of the battery, and analyzes a change in the internal resistance of the battery according to a temperature change of the battery and a state of charge (SoC) of the battery at the measured charge/discharge rate (C-rate) of the battery to predict deterioration of the battery.
  • C-rate charge/discharge rate
  • the present invention has the following excellent effects.
  • the internal resistance value of a battery cell is calculated based on the average value of the effective value of the voltage change value of the battery cell and the effective value of the current change value of the battery cell, thereby improving the accuracy of calculating the internal resistance of the battery, thereby improving the accuracy of battery status diagnosis regardless of the battery operating state.
  • the calculated internal resistance value of the battery according to the measured temperature and state of charge of the battery can be analyzed to predict the deterioration of the battery, thereby determining the residual value of the battery and enabling upcycling of waste batteries for future reuse, thereby having the advantage of reducing environmental pollution caused by waste batteries.
  • FIG. 1 is a drawing for explaining a battery diagnosis program using the internal resistance of a battery stored in a recording medium according to one embodiment of the present invention.
  • FIG. 2 is a graph for explaining battery internal resistance calculation in a battery internal resistance calculation means of a battery diagnosis program using battery internal resistance stored in a recording medium according to one embodiment of the present invention.
  • FIG. 3 is a graph for explaining battery deterioration prediction in a battery deterioration prediction means of a battery diagnosis program using battery internal resistance stored in a recording medium according to one embodiment of the present invention.
  • FIG. 4 is a configuration diagram for explaining a battery diagnosis system to which a battery diagnosis program using the internal resistance of a battery stored in a recording medium according to one embodiment of the present invention is applied.
  • FIG. 5 is a configuration diagram for explaining a mobile battery diagnosis system to which a battery diagnosis program using the internal resistance of a battery stored in a recording medium according to one embodiment of the present invention is applied.
  • FIG. 1 is a diagram for explaining a battery diagnosis program using the internal resistance of a battery stored in a recording medium according to one embodiment of the present invention.
  • a battery diagnosis program (1000) using the internal resistance of a battery stored in a recording medium of the present invention is a battery diagnosis program that calculates the internal resistance of a battery based on data measuring voltage, current, and temperature of a battery cell to be diagnosed, analyzes the calculated internal resistance of the battery, and diagnoses the state of the battery, i.e., the remaining life, with high precision without being affected by the operating state of the battery (charge/discharge, stop, standby, etc.).
  • the battery diagnosis program (1000) using the internal resistance of the battery stored in the recording medium of the present invention diagnoses the state of the battery, i.e., the remaining life, by receiving data measured directly by the administrator through a separate measuring device, such as voltage, current, and temperature of the battery cell, or voltage, current, and temperature data of the battery cell measured by the battery management system.
  • the battery diagnosis program (1000) using the internal resistance of the battery stored in the recording medium of the present invention can transmit the battery status diagnosis result to a display for battery monitoring or a portable terminal of an external manager.
  • the present invention can separately provide only a server in which a battery diagnosis program (1000) using the internal resistance of a battery stored in a recording medium is stored.
  • a battery diagnostic program (1000) using the internal resistance of the battery stored in the above-mentioned recording medium can be stored and provided in various computers in addition to the above-mentioned server.
  • the computer is a broad computer that includes not only a general personal computer, but also a server computer that can be accessed via a communication network, a cloud system, smart devices such as smartphones and tablets, and an embedded system.
  • the battery diagnosis program (1000) using the internal resistance of the battery may be provided by being stored in a separate recording medium, and the recording medium may be one specially designed and configured for the present invention or one known to and usable by a person having ordinary knowledge in the computer software field.
  • the recording medium may be a hardware device specifically configured to store and execute program instructions, alone or in combination, such as a magnetic medium such as a hard disk, a floppy disk, and a magnetic tape, an optical recording medium such as a CD or a DVD, a magneto-optical recording medium capable of both magnetic and optical recording, a ROM, a RAM, a flash memory, etc.
  • the battery diagnostic program (1000) using the internal resistance of the battery stored in the above-mentioned recording medium may be a program composed of program commands, local data files, local data structures, etc., either singly or in combination, and may be a program written in a high-level language code that can be executed by a computer using an interpreter, etc., as well as machine language code created by a compiler.
  • a battery diagnosis program (1000) using the internal resistance of a battery stored in the above-mentioned recording medium comprises a data collection means (1100), a battery internal resistance calculation means (1200), a battery heat generation prediction means (1300), a battery deterioration prediction means (1400), and a battery status diagnosis means (1500).
  • the data collection means (1100) collects voltage data, current data, and temperature data of battery cells measured in the battery to be diagnosed.
  • the above battery internal resistance calculation means (1200) calculates the internal resistance of the battery using voltage data and current data of the battery cell.
  • the battery internal resistance calculation means (1200) calculates the internal resistance (Rs) of the battery by using the root mean square (Vrms) for the voltage change values of the battery cell measured in the battery and the root mean square (Irms) for the current change values when an AC signal is periodically generated by the operation of continuously turning the switch of the battery ON/OFF.
  • the internal resistance (Rs) of the battery is calculated as the root mean square value of the voltage change (Vrms)/the root mean square value of the current change (Irms).
  • the battery internal resistance calculation means (1200) of the present invention has the advantage of improving the problem of low diagnosis accuracy due to variables caused by various external factors and an increased error range due to a high charge/discharge rate (C-rate) caused by a high load of the battery, and of being able to diagnose the status of the battery without being affected by the operating status of the battery.
  • C-rate charge/discharge rate
  • the battery internal resistance calculation means (1200) performs a task of repeatedly classifying the calculated battery internal resistance data into database statistics to determine the final battery internal resistance value in order to improve the accuracy of the battery condition diagnosis, thereby performing a correction to minimize the error of the battery internal resistance value, thereby improving the accuracy of the battery internal resistance calculation result.
  • FIG. 2 is a graph for explaining battery internal resistance calculation in a battery internal resistance calculation means of a battery diagnosis program using battery internal resistance stored in a recording medium according to one embodiment of the present invention.
  • the graph in FIG. 2 is an example graph showing a change in voltage over time during signal exchange of the battery when the temperature of the battery cell is 25 degrees and the state of charge is 0.5. Specifically, it is an example graph deriving a total internal resistance (R i ) value of the battery according to the temperature change of the battery and the state of charge (SoC) of the battery under various charge/discharge rate (C-rate) conditions of the battery using direct current internal resistance (DCIR).
  • R i total internal resistance
  • SoC state of charge
  • DCIR direct current internal resistance
  • the battery internal resistance calculation means (1200) calculates the total internal resistance (R i ) of the battery by adding the Ohmic resistance (R O ), charge transfer resistance (R ct ), and diffusion resistance (R d ) appearing in the battery.
  • the above battery heat generation prediction means (1300) predicts the temperature of the battery during charging and discharging using temperature data measured from the battery cell, thereby predicting the heat generation of the battery.
  • the heat generation prediction means (1300) predicts the battery heat generation using a battery heat generation prediction model generated by learning the correlation between the anisotropic heat transfer properties of jelly rolls according to various types of batteries, the electrical and thermal characteristics of the battery cell itself, and the temperature change data during charging and discharging of the battery.
  • the jelly roll refers to a laminated structure of multiple layers of the positive electrode, negative electrode, current collector, and separator that constitute the battery, and has unique electrical/thermal properties depending on the type of battery.
  • the battery heat generation prediction model is a learning model for heat generation prediction generated by learning the battery's status data and characteristic data based on big data and deep learning.
  • the battery heat generation prediction means (1300) predicts the total heat generation of the battery, including reversible heat generation occurring within the battery and irreversible heat generation caused by external influence.
  • the battery heat generation prediction means (1300) can predict the heat generation of the battery by analyzing the characteristics of a lumped heat region rather than analyzing the entire jelly roll area of the battery, thereby minimizing the amount of prediction calculation and shortening the calculation time.
  • the above battery deterioration prediction means (1400) predicts deterioration of the battery based on battery internal resistance calculation data calculated from the battery internal resistance calculation means (1200) and battery heat generation prediction data derived from the battery heat generation prediction means (1300).
  • FIG. 3 is a graph for explaining battery deterioration prediction in a battery deterioration prediction means of a battery diagnosis program using battery internal resistance stored in a recording medium according to one embodiment of the present invention.
  • the battery deterioration prediction means (1400) predicts deterioration of the battery by using a battery deterioration prediction model that analyzes the temperature of the battery derived from the battery heat generation prediction model of the battery heat generation prediction means (1300) according to the charge/discharge rate (C-rate) of the battery and the change in internal resistance of the battery according to the state of charge (SoC) of the battery.
  • C-rate charge/discharge rate
  • SoC state of charge
  • the battery deterioration prediction model is a learning model for predicting deterioration of the battery generated by learning temperature change data of the battery, internal resistance change data of the battery, and status data of the battery based on big data and deep learning.
  • the above battery condition diagnosis means (1500) predicts the aging degree of the battery according to charging and discharging and the remaining life of the battery based on the deterioration prediction result of the battery derived from the battery deterioration prediction means (1400), analyzes the same, and ultimately diagnoses the internal health (state of health, SOH) of the battery.
  • the present invention has the advantage of reducing environmental pollution caused by waste batteries because it can predict the residual value of the battery and thus upcycle waste batteries for future reuse.
  • the present invention can be provided as a battery diagnosis system (100) to which a battery diagnosis program (1000) using the internal resistance of a battery stored in a recording medium is applied.
  • FIG. 4 is a configuration diagram for explaining a battery diagnosis system to which a battery diagnosis program using internal resistance of a battery stored in a recording medium according to an embodiment of the present invention is applied
  • FIG. 5 is a configuration diagram for explaining a mobile battery diagnosis system to which a battery diagnosis program using internal resistance of a battery stored in a recording medium according to an embodiment of the present invention is applied
  • FIG. 6 is a configuration diagram for explaining a battery diagnosis system combined with an electric vehicle charger to which a battery diagnosis program using internal resistance of a battery stored in a recording medium according to an embodiment of the present invention is applied.
  • the battery diagnosis system (100) of the present invention is a system that can measure the state of the battery, analyze the measured data, and diagnose and monitor the state of the battery.
  • the above battery diagnosis system (100) is largely composed of a battery status measurement module, a battery status diagnosis module, and a battery status monitoring module.
  • the above battery status measurement module comprises an impedance measurement module for measuring the impedance of the battery, a measurement module for measuring battery voltage, current, and temperature, and a battery status analysis module for analyzing the battery status.
  • the above battery status diagnosis module analyzes the characteristics of the battery based on the data measured and derived from the above battery status measurement module and analyzes the correlation between the data to diagnose the status of the battery.
  • the battery status diagnosis module diagnoses the status of the battery using a battery diagnosis program (1000) that utilizes the internal resistance of the battery stored in a recording medium.
  • the battery status diagnosis module may be a server in which a battery diagnosis program (1000) using the internal resistance of the battery stored in the recording medium is stored.
  • the above battery status monitoring module is a means for monitoring the safety of the battery based on data measuring the status of the battery and data diagnosing the status of the battery, and monitors whether the battery status is outside a range preset by the administrator, and if it is outside the preset range, can provide a function for notifying the administrator of the status of the battery.
  • the battery diagnosis system (100) can be provided as a mobile battery diagnosis system in which the battery diagnosis system (100) is mounted on a dedicated transport vehicle.
  • the mobile battery diagnostic system be used for battery diagnosis at OEMs, insurance companies (emergency dispatch), car centers, and junkyards.
  • the battery diagnosis program (1000) using the internal resistance of the battery stored in the recording medium of the present invention can predict the deterioration of the battery by analyzing the internal resistance value of the battery calculated according to the measured temperature and state of charge of the battery, thereby predicting the aging degree and residual value of the battery and reducing the environmental pollution caused by the waste batteries because waste batteries can be upcycled for future reuse.
  • Battery Diagnostic System 1000 Battery Diagnostic Program
  • Data collection means 1200 Battery internal resistance calculation means
  • Battery heating prediction means 1400 Battery deterioration prediction means
  • the battery diagnosis program using the internal resistance of the battery stored in the recording medium of the present invention can be industrially utilized in the field of waste battery recycling, where waste batteries that can have a harmful effect on the health of people, living things, and the environment are also increasing due to the rapidly increasing spread of electric vehicles, and the remaining life of the waste batteries can be diagnosed and reused.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Chemical & Material Sciences (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Electrochemistry (AREA)
  • General Chemical & Material Sciences (AREA)
  • Tests Of Electric Status Of Batteries (AREA)
  • Secondary Cells (AREA)

Abstract

La présente invention concerne un programme de diagnostic de batterie utilisant une résistance interne de batterie stockée dans un support d'enregistrement et, plus spécifiquement, un programme de diagnostic de batterie utilisant une résistance interne de batterie stockée dans un support d'enregistrement, le programme étant apte à prédire la détérioration d'une batterie et diagnostiquer la santé interne de la batterie par l'analyse d'une variation de température de la batterie et d'une variation de résistance interne de batterie selon un état de charge (SOC) de la batterie sur la base d'une vitesse de charge et de décharge (C-rate) de la batterie devant être diagnostiquée.
PCT/KR2023/019892 2023-11-10 2023-12-05 Programme de diagnostic de batterie utilisant une résistance interne de batterie stockée dans un support d'enregistrement Pending WO2025100624A1 (fr)

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KR10-2023-0155595 2023-11-10
KR1020230155595A KR102892976B1 (ko) 2023-11-10 2023-11-10 기록 매체에 저장된 배터리 내부저항을 이용한 배터리 진단 프로그램

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KR20220038789A (ko) * 2019-08-08 2022-03-29 트와이스 테크놀로지스 게엠베하 배터리 시뮬레이션
KR20230067793A (ko) * 2021-11-09 2023-05-17 한국전자기술연구원 배터리 내부저항 측정 장치 및 방법
KR20230111135A (ko) * 2022-01-17 2023-07-25 르네사스 일렉트로닉스 가부시키가이샤 반도체 장치 및 배터리의 충전 제어 방법

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20070051916A (ko) * 2004-08-25 2007-05-18 닛본 덴끼 가부시끼가이샤 내부 임피던스 검출 장치, 내부 임피던스 검출 방법,열화도 검출 장치 및 열화도 검출 방법
KR20220038789A (ko) * 2019-08-08 2022-03-29 트와이스 테크놀로지스 게엠베하 배터리 시뮬레이션
KR20210089021A (ko) * 2020-01-07 2021-07-15 주식회사 엘지에너지솔루션 시뮬레이션 시스템 및 데이터 분산 방법
KR20230067793A (ko) * 2021-11-09 2023-05-17 한국전자기술연구원 배터리 내부저항 측정 장치 및 방법
KR20230111135A (ko) * 2022-01-17 2023-07-25 르네사스 일렉트로닉스 가부시키가이샤 반도체 장치 및 배터리의 충전 제어 방법

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