WO2023132520A1 - 배터리 용량 예측 장치 및 그것의 동작 방법 - Google Patents

배터리 용량 예측 장치 및 그것의 동작 방법 Download PDF

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Publication number
WO2023132520A1
WO2023132520A1 PCT/KR2022/020745 KR2022020745W WO2023132520A1 WO 2023132520 A1 WO2023132520 A1 WO 2023132520A1 KR 2022020745 W KR2022020745 W KR 2022020745W WO 2023132520 A1 WO2023132520 A1 WO 2023132520A1
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WIPO (PCT)
Prior art keywords
capacity
battery
change
data
comparison
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Ceased
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PCT/KR2022/020745
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English (en)
French (fr)
Korean (ko)
Inventor
최정환
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LG Energy Solution Ltd
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LG Energy Solution Ltd
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Application filed by LG Energy Solution Ltd filed Critical LG Energy Solution Ltd
Priority to CN202280077440.XA priority Critical patent/CN118284817A/zh
Priority to JP2024540631A priority patent/JP2025502012A/ja
Priority to EP22919057.4A priority patent/EP4425198B1/en
Priority to ES22919057T priority patent/ES3055131T3/es
Priority to US18/710,610 priority patent/US20250012862A1/en
Publication of WO2023132520A1 publication Critical patent/WO2023132520A1/ko
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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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]
    • G01R31/392—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]
    • G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • 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
    • G01R19/0038—Circuits for comparing several input signals and for indicating the result of this comparison, e.g. equal, different, greater, smaller (comparing pulses or pulse trains according to amplitude)
    • 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
    • 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
    • G01R31/387—Determining ampere-hour charge capacity or SoC
    • 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
    • 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]
    • G01R31/374—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] with means for correcting the measurement for temperature or ageing
    • 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

  • Embodiments disclosed in this document relate to an apparatus for predicting battery capacity and an operation method thereof.
  • Electric vehicles receive power from the outside to charge the battery cells, and then drive the motor with the voltage charged in the battery cells to obtain power.
  • Battery cells of electric vehicles may generate heat due to chemical reactions occurring in the process of charging and discharging electricity, and such heat may damage the performance and lifespan of the battery cells.
  • One object of the embodiments disclosed in this document is to provide a battery capacity prediction device and its operating method capable of diagnosing a rapid capacity reduction phenomenon of a battery in advance by analyzing the capacity reduction of the battery in various temperature, current, and voltage ranges. is to provide
  • An apparatus for predicting battery capacity extracts comparison data obtained by comparing the measured capacity of the battery with reference capacity of the battery, and changes in capacity obtained by measuring the change in capacity of the battery according to the cycle change of the battery. It may include an extraction unit that extracts data and a controller that predicts the capacity of the battery based on the comparison data and the capacity change data.
  • the extraction unit may extract a comparison value obtained by comparing the measured capacity of the battery to the reference capacity of the battery measured through a reference performance test (RPT).
  • RPT reference performance test
  • the extractor may measure a change in the comparison value according to a change in temperature of the battery or a change in the comparison value according to a change in current of the battery.
  • the controller may predict the capacity of the battery under a standard performance test condition based on the capacity change data and the comparison value.
  • the controller may estimate the capacity of the battery under a full equivalent cycle (FEC) condition by converting the reference capacity into a nominal capacity of the battery.
  • FEC full equivalent cycle
  • the controller may extract a capacity change pattern of the battery based on the capacity of the battery in the equivalent cycle condition.
  • the controller extracts a capacity change pattern of the battery and analyzes a capacity change pattern immediately after a standard performance test of the battery, a normal capacity change pattern, and a rapid capacity degradation pattern.
  • An operating method of an apparatus for predicting battery capacity includes extracting comparison data by comparing a measured capacity of a battery with a reference capacity of the battery, and measuring a change in capacity of the battery according to a change in cycles of the battery.
  • the capacity of the battery may be predicted based on the step of measuring and the comparison data and the capacity change data.
  • the step of comparing the measured capacity of the battery with respect to the reference capacity of the battery and extracting the comparison data is the comparison of the reference capacity of the battery measured through a reference performance test (RPT) of the battery. Comparative values can be extracted by comparing measured capacities.
  • the step of comparing the measured capacity of the battery to the reference capacity of the battery and extracting comparison data may include a change in the comparison value according to a change in the temperature of the battery or a change in the current of the battery. change can be measured.
  • the predicting the capacity of the battery based on the comparison data and the capacity change data may include predicting the capacity of the battery under a reference performance test condition based on the capacity change data and the comparison value. there is.
  • the step of predicting the capacity of the battery based on the comparison data and the capacity change data may include converting the reference capacity into a nominal capacity of the battery to perform an equivalent cycle (FEC, Full Equivalent Cycle). ) can predict the capacity of the battery under the condition.
  • FEC Full Equivalent Cycle
  • the predicting the capacity of the battery based on the comparison data and the capacity change data may extract a capacity change pattern of the battery based on the capacity of the battery in the equivalent cycle condition.
  • the step of predicting the capacity of the battery based on the comparison data and the capacity change data may include extracting a capacity change pattern of the battery, a capacity change pattern immediately after a standard performance test, and a normal capacity change of the battery. Patterns and rapid capacity decay patterns can be analyzed.
  • rapid capacity reduction of a battery can be diagnosed in advance by analyzing capacity reduction of a battery in various temperature, current, and voltage ranges.
  • a battery capacity prediction device and its operating method may be provided.
  • FIG. 1 is a diagram showing a battery pack according to an embodiment disclosed in this document.
  • FIG. 2 is a block diagram showing the configuration of an apparatus for predicting battery capacity according to an embodiment disclosed in this document.
  • FIG. 3 is a graph showing changes in capacity data of a battery and changes in reference capacity data according to a change in cycles of a battery according to an embodiment disclosed herein.
  • 4A is a graph showing a change in a comparison value according to a change in temperature of a battery according to an embodiment described in the present document.
  • 4B is a graph showing a change in a comparison value according to a change in current of a battery according to an embodiment described in the present document.
  • FIG. 5 is a graph showing a change in capacity degradation amount per cycle of a battery according to a change in cycle of the battery according to an embodiment described in the present document.
  • 6A is a graph showing a battery capacity change pattern according to a battery equivalent cycle change according to an embodiment described herein.
  • 6B is a graph showing a change in capacity of a battery according to a change in equivalent cycle of the battery according to an embodiment described in the present document.
  • FIG. 7 is a flowchart illustrating an operating method of an apparatus for predicting battery capacity according to an embodiment disclosed in this document.
  • FIG. 8 is a block diagram illustrating a hardware configuration of a computing system implementing an apparatus for predicting battery capacity according to an embodiment disclosed in this document.
  • FIG. 1 is a diagram showing a battery pack according to an embodiment disclosed in this document.
  • a battery pack 1000 may include a battery module 100, a battery capacity estimation device 200, and a relay 300.
  • the battery module 100 may include a plurality of battery cells 110 , 120 , 130 , and 140 . Although the number of battery cells is illustrated in FIG. 1 as four, it is not limited thereto, and the battery module 100 may include n (n is a natural number equal to or greater than 2) battery cells.
  • the battery module 100 may supply power to a target device (not shown). To this end, the battery module 100 may be electrically connected to the target device.
  • the target device may include an electrical, electronic, or mechanical device operated by receiving power from the battery pack 1000 including the plurality of battery cells 110, 120, 130, and 140, for example ,
  • the target device may be an electric vehicle (EV) or an energy storage system (ESS), but is not limited thereto.
  • the plurality of battery cells 110, 120, 130, and 140 are basic units of a battery capable of charging and discharging electrical energy, such as a lithium ion battery, a lithium ion polymer battery, a nickel It may be a cadmium (Ni-Cd) battery, a nickel hydrogen (Ni-MH) battery, etc., but is not limited thereto.
  • a battery capable of charging and discharging electrical energy such as a lithium ion battery, a lithium ion polymer battery, a nickel It may be a cadmium (Ni-Cd) battery, a nickel hydrogen (Ni-MH) battery, etc., but is not limited thereto.
  • FIG. 1 shows a case in which one battery module 100 is provided, a plurality of battery modules 100 may be configured according to embodiments.
  • the battery capacity estimation apparatus 200 may predict the capacity of the plurality of battery cells 110, 120, 130, and 140 based on the temperature, current, and voltage data of the plurality of battery cells 110, 120, 130, and 140. .
  • the battery capacity prediction apparatus 200 calculates the capacity of the plurality of battery cells 110, 120, 130, and 140 for each temperature, current, and voltage of the battery based on the battery data of the plurality of battery cells 110, 120, 130, and 140. can predict
  • the battery capacity estimation device 200 may be implemented in the form of a battery management system (BMS). Also, according to embodiments, the battery capacity estimation device 200 may be installed in a battery management device.
  • BMS battery management system
  • the battery management device may manage and/or control the state and/or operation of the battery module 100 .
  • the battery management device may manage and/or control states and/or operations of the plurality of battery cells 110 , 120 , 130 , and 140 included in the battery module 100 .
  • the battery management device may manage charging and/or discharging of the battery module 100 .
  • the battery management device may monitor the battery module 100 and/or the voltage, current, and temperature of each of the plurality of battery cells 110, 120, 130, and 140 included in the battery module 100.
  • sensors or various measurement modules may be additionally installed in the battery module 100, a charge/discharge path, or an arbitrary position of the battery module 100.
  • the battery management device may calculate a parameter representing the state of the battery module 100, for example, SOC (State of Charge) or SOH (State of Health), based on measured values such as monitored voltage, current, and temperature. there is.
  • the battery management device may control the operation of the relay 300 .
  • the battery management device may short the relay 300 to supply power to the target device.
  • the battery management device may short-circuit the relay 300 when a charging device is connected to the battery pack 1000 .
  • the battery management device may calculate a cell balancing time of each of the plurality of battery cells 110 , 120 , 130 , and 140 .
  • the cell balancing time may be defined as a time required for balancing battery cells.
  • the battery management apparatus may calculate a cell balancing time based on a state of charge (SOC), battery capacity, and balancing efficiency of each of the plurality of battery cells 110 , 120 , 130 , and 140 .
  • SOC state of charge
  • FIG. 2 is a block diagram showing the configuration of a battery capacity prediction device according to an embodiment disclosed in this document.
  • the battery capacity estimation apparatus 200 may include an extractor 210 and a controller 220 .
  • the extractor 210 may obtain capacity data C obtained by measuring the capacity of the plurality of battery cells 110 , 120 , 130 , and 140 .
  • the extractor 210 receives reference capacity data obtained by measuring reference capacities of the plurality of battery cells 110, 120, 130, and 140. can be obtained.
  • the reference capacity is the capacity of the battery measured through a reference performance test (RPT).
  • the standard performance test may periodically measure the life or capacity of a battery under conditions of a specific temperature, specific current, and specific voltage range in order to check the deterioration performance of a target device.
  • the standard performance test may repeat charging and discharging under specific temperature and specific current conditions until the battery reaches a voltage value in which the SOC of the battery is 0% and a voltage value in which the SOC of the battery is 100%. .
  • the extractor 210 extracts reference capacity data of a plurality of battery cells 110, 120, 130, and 140.
  • the reference capacity of the plurality of battery cells 110, 120, 130, and 140 is compared with the measured capacity data C of the plurality of battery cells 110, 120, 130, and 140.
  • Comparison data obtained by comparing measured capacities (C) of the plurality of battery cells 110 , 120 , 130 , and 140 may be extracted.
  • the extraction unit 210 is the reference capacity of the plurality of battery cells (110, 120, 130, 140) Comparison value comparing the measured capacities (C) of the plurality of battery cells 110, 120, 130, and 140 can be extracted.
  • 4A is a graph showing a change in a comparison value according to a change in temperature of a battery according to an embodiment described in the present document.
  • 4B is a graph showing a change in a comparison value according to a change in current of a battery according to an embodiment described in the present document.
  • the extraction unit 210 may generate a graph showing a change in a comparison value according to a temperature change of the plurality of battery cells 110 , 120 , 130 , and 140 .
  • the extraction unit 210 provides a comparison value according to a change in current of the plurality of battery cells 110, 120, 130, and 140.
  • a graph showing the change in can be created.
  • the extraction unit 210 provides a comparison value according to a temperature change of the plurality of battery cells 110, 120, 130, or 140 or a current change of the plurality of battery cells 110, 120, 130, or 140.
  • a comparison value according to temperature change of the plurality of battery cells 110, 120, 130, and 140 by analyzing the change in Comparison value according to the change of or the change of the current of the battery change trend can be measured.
  • the extractor 210 may measure a capacity change per cycle of the plurality of battery cells 110, 120, 130, and 140 according to a cycle change of the plurality of battery cells 110, 120, 130, and 140. That is, the extractor 210 determines the amount of capacity degradation per cycle of the plurality of battery cells 110, 120, 130, and 140 according to the cycle change of the plurality of battery cells 110, 120, 130, and 140. can measure
  • the extractor 210 may extract capacity change data obtained by measuring a change in capacity of a battery per cycle according to a change in cycles of the plurality of battery cells 110 , 120 , 130 , and 140 .
  • the extraction unit 210 determines the capacity when the number of cycle repetitions of the plurality of battery cells 110, 120, 130, and 140 is n. , and the capacity of the plurality of battery cells 110, 120, 130, and 140 before k cycles
  • the capacity degradation per cycle of the plurality of battery cells 110, 120, 130, and 140 can be calculated with
  • the extraction unit 210 determines the amount of capacity degradation per cycle of the plurality of battery cells 110, 120, 130, and 140 according to the cycle change of the plurality of battery cells 110, 120, 130, and 140. It is possible to extract capacity change data representing a change in .
  • the controller 220 may predict the capacities of the plurality of battery cells 110 , 120 , 130 , and 140 based on the comparison data and the capacitance change data. Specifically, the controller 220 may predict a change in capacity of the plurality of battery cells 110 , 120 , 130 , and 140 under a standard performance test condition based on the change in capacity data and the comparison value.
  • the controller 210 determines the amount of capacity degradation per cycle of the plurality of battery cells 110, 120, 130, and 140.
  • the reciprocal of the value compared to multiplied by may be calculated as a capacity change rate of the plurality of battery cells 110, 120, 130, and 140 under the standard performance test condition.
  • the controller 220 sets the reference capacities of the plurality of battery cells based on the capacities of the plurality of battery cells 110, 120, 130, and 140 under the predicted reference performance test condition as the nominal capacity of the plurality of battery cells. By converting to , it is possible to predict the capacity of a plurality of battery cells in an equivalent cycle (FEC, Full Equivalent Cycle) condition.
  • FEC Full Equivalent Cycle
  • the controller 220 determines the amount of capacity degradation per cycle of the plurality of battery cells 110, 120, 130, and 140 under the standard performance test condition.
  • the nominal capacity of the battery cells 110, 120, 130, and 140 compared to the measured capacity (C) of the plurality of battery cells 110, 120, 130, and 140 in the value compared to
  • FEC equivalent cycle
  • the controller 220 controls the small capacity degradation of the plurality of battery cells 110, 120, 130, and 140. In order to increase the value of k, several multiples can be selected.
  • the controller 220 may extract a battery capacity change pattern based on the battery capacity in an equivalent cycle condition.
  • 6A is a graph showing a change pattern of capacity of a battery according to a change in equivalent cycle of the battery according to an embodiment described in the present document.
  • the controller 220 determines the amount of capacity degradation of the plurality of battery cells 110, 120, 130, and 140 under an equivalent cycle (FEC) condition.
  • FEC equivalent cycle
  • the controller 220 may extract and analyze pattern A, pattern B, pattern C, and pattern D, which are capacitance change patterns of the plurality of battery cells 110, 120, 130, and 140.
  • the A pattern calculated by the controller 220 is a pattern that appears when the deterioration rate of the plurality of battery cells 110, 120, 130, and 140 decreases. 140) may appear in the battery cycle immediately after the criterion performance test.
  • the controller 220 may analyze the A pattern as a capacity change pattern that appears according to a difference in temperature or current of the plurality of battery cells 110 , 120 , 130 , and 140 .
  • the C pattern calculated by the controller 220 may be analyzed as a pattern that appears when the deterioration rates of the plurality of battery cells 110, 120, 130, and 140 are constant.
  • the controller 220 may analyze the C pattern as a capacity change pattern that appears when the loss of active material (LAM) of the plurality of battery cells 110 , 120 , 130 , and 140 linearly degenerates.
  • LAM loss of active material
  • the D pattern calculated by the controller 220 may be analyzed as a pattern appearing when the deterioration rate of the plurality of battery cells 110, 120, 130, and 140 is accelerated.
  • the controller 220 adjusts the D pattern to a plurality of battery cells 110, 120, 130, 140 due to rapid decrease in Lithium Plating or Electrolyte, thereby reducing the capacity of the plurality of battery cells 110, 120, 130, 140 to Exponential. patterns can be analyzed.
  • FIG. 6B is a graph showing a change in capacity of a battery according to a change in equivalent cycle of the battery according to an embodiment described in the present document.
  • the controller 220 may collect a battery capacity change pattern according to an equivalent cycle change of various batteries shown in FIG. 6A and extract a graph showing a battery capacity change according to an equivalent cycle change of the battery.
  • the controller 220 determines the capacity change pattern of the plurality of battery cells 110, 120, 130, and 140 immediately after the standard performance test and the normal capacity change of the plurality of battery cells 110, 120, 130, and 140 based on FIG. 6B. Patterns and rapid capacity degradation patterns of the plurality of battery cells 110 , 120 , 130 , and 140 may be analyzed.
  • rapid capacity reduction of the battery can be diagnosed in advance by analyzing the capacity reduction of the battery in various temperature, current, and voltage sections.
  • the battery capacity prediction device 200 can more accurately diagnose the rapid deterioration of battery capacity in advance, thereby improving the effectiveness and stability of battery management.
  • the battery capacity predicting apparatus 200 may extract a battery capacity change pattern by defining a relationship between a battery standard capacity measured through a standard performance test and a battery deterioration cycle.
  • FIG. 7 is a flowchart illustrating an operating method of an apparatus for predicting battery capacity according to an embodiment disclosed in this document.
  • the battery capacity estimating apparatus 200 may be substantially the same as the battery capacity estimating apparatus 200 described with reference to FIGS. 1 to 6 , a brief description will be made hereinafter to avoid duplication of description.
  • the operating method of the battery capacity prediction device 200 compares the measured capacity of the battery to the reference capacity of the battery and extracts comparison data (S101), and measures the change in capacity of the battery according to the cycle change of the battery. It may include measuring (S102) and estimating the capacity of the battery based on the comparison data and the capacity change data (S103).
  • the extractor 210 collects reference capacity data obtained by measuring reference capacities of the plurality of battery cells 110, 120, 130, and 140. can be obtained.
  • the reference capacity is the capacity of the battery measured through a reference performance test (RPT).
  • the standard performance test may periodically measure the life or capacity of a battery under conditions of a specific temperature, specific current, and specific voltage range in order to check the deterioration performance of a target device.
  • the standard performance test may repeat charging and discharging under specific temperature and specific current conditions until the battery reaches a voltage value in which the SOC of the battery is 0% and a voltage value in which the SOC of the battery is 100%. .
  • step S101 the extractor 210 extracts the reference capacity data of the plurality of battery cells 110, 120, 130, and 140.
  • the reference capacity of the plurality of battery cells 110, 120, 130, and 140 is compared with the measured capacity data C of the plurality of battery cells 110, 120, 130, and 140.
  • Comparison data obtained by comparing measured capacities (C) of the plurality of battery cells 110 , 120 , 130 , and 140 may be extracted.
  • step S101 in detail, the extraction unit 210 extracts the reference capacities of the plurality of battery cells 110, 120, 130, and 140. Comparison value comparing the measured capacities (C) of the plurality of battery cells 110, 120, 130, and 140 can be extracted.
  • the extraction unit 210 may generate a graph representing a change in a comparison value according to a temperature change of the plurality of battery cells 110 , 120 , 130 , and 140 .
  • the extraction unit 210 extracts a comparison value according to a change in current of the plurality of battery cells 110, 120, 130, and 140.
  • a graph showing the change in can be created.
  • the extraction unit 210 extracts a comparison value according to a change in temperature of the plurality of battery cells 110, 120, 130, or 140 or a change in current of the plurality of battery cells 110, 120, 130, or 140.
  • a comparison value according to the temperature change of the plurality of battery cells 110, 120, 130, and 140 by analyzing the change in Comparison value according to the change of or the change of battery current change trend can be measured.
  • the extraction unit 210 may measure the amount of change in capacity per cycle of the plurality of battery cells 110, 120, 130, and 140 according to the cycle change of the plurality of battery cells 110, 120, 130, and 140. there is. In step S102, the extraction unit 210 determines the amount of capacity degradation per cycle of the plurality of battery cells 110, 120, 130, and 140 according to the cycle change of the plurality of battery cells 110, 120, 130, and 140. can measure
  • the controller 220 may predict the capacity of the plurality of battery cells 110 , 120 , 130 , and 140 based on the comparison data and the capacity change data. In step S103 , the controller 220 may predict a change in capacity of the plurality of battery cells 110 , 120 , 130 , and 140 under a standard performance test condition based on the change in capacity data and the comparison value.
  • step S103 the controller 210 determines the amount of capacity degradation per cycle of the plurality of battery cells 110, 120, 130, and 140.
  • the reciprocal of the value compared to multiplied by may be calculated as a capacity change rate of the plurality of battery cells 110, 120, 130, and 140 under the standard performance test condition.
  • step S103 the controller 220 sets the nominal capacity of the plurality of battery cells based on the capacities of the plurality of battery cells 110, 120, 130, and 140 under the predicted reference performance test condition.
  • the capacity of a plurality of battery cells can be estimated by converting to (Nominal Capacity) under an equivalent cycle (FEC, Full Equivalent Cycle) condition.
  • step S103 the controller 220 determines the amount of capacity degradation per cycle of the plurality of battery cells 110, 120, 130, and 140 under the reference performance test condition.
  • the nominal capacity of the battery cells 110, 120, 130, and 140 compared to the measured capacity (C) of the plurality of battery cells 110, 120, 130, and 140 in the value compared to
  • FEC equivalent cycle
  • step S103 the controller 220 may extract a battery capacity change pattern based on the battery capacity in an equivalent cycle condition.
  • the controller 220 may collect a pattern of change in battery capacity according to a change in the equivalent cycle of the battery and extract a graph representing a change in capacity of the battery according to a change in the equivalent cycle of the battery.
  • step S103 the controller 220 determines the capacity change pattern immediately after the reference performance test of the plurality of battery cells 110, 120, 130, and 140, and the normal capacity change pattern of the plurality of battery cells 110, 120, 130, and 140. And a rapid capacity degradation pattern of the plurality of battery cells 110 , 120 , 130 , and 140 may be analyzed.
  • FIG. 8 is a block diagram illustrating a hardware configuration of a computing system implementing an apparatus for predicting battery capacity according to an embodiment disclosed in this document.
  • a computing system 2000 may include an MCU 2100, a memory 2200, an input/output I/F 2300 and a communication I/F 2400. there is.
  • the MCU 2100 executes various programs (eg, a battery capacity estimation function) stored in the memory 2200, processes these programs various data, and the battery capacity estimation apparatus 200 shown in FIG. 1 described above. ) It may be a processor that performs the functions of.
  • programs eg, a battery capacity estimation function
  • It may be a processor that performs the functions of.
  • the memory 2200 may store various programs related to the operation of the facility control device 200 . Also, the memory 2200 may store operation data of the facility control device 200 .
  • the memory 2200 may be a volatile memory or a non-volatile memory.
  • the memory 2200 as a volatile memory may be RAM, DRAM, SRAM, or the like.
  • the memory 2200 as a non-volatile memory may be ROM, PROM, EAROM, EPROM, EEPROM, flash memory, or the like. Examples of the above-listed memories 2200 are merely examples and are not limited to these examples.
  • the input/output I/F 2300 is an interface that connects an input device (not shown) such as a keyboard, mouse, or touch panel, an output device such as a display (not shown), and the MCU 2100 to transmit and receive data. can provide.
  • an input device such as a keyboard, mouse, or touch panel
  • an output device such as a display (not shown)
  • the MCU 2100 to transmit and receive data. can provide.
  • the communication I/F 2400 is a component capable of transmitting and receiving various types of data with a server, and may be various devices capable of supporting wired or wireless communication. For example, through the communication I/F 2400, it is possible to transmit/receive programs or various data for resistance measurement and abnormality diagnosis from a separately provided external server.
  • the computer program according to an embodiment disclosed in this document is recorded in the memory 2200 and processed by the MCU 2100, for example, the battery capacity predicting device 200 described with reference to FIGS. 1 and 2 ) may be implemented as a module that performs each function.

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  • Secondary Cells (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
  • Testing Electric Properties And Detecting Electric Faults (AREA)
  • Tests Of Electric Status Of Batteries (AREA)
PCT/KR2022/020745 2022-01-07 2022-12-19 배터리 용량 예측 장치 및 그것의 동작 방법 Ceased WO2023132520A1 (ko)

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EP22919057.4A EP4425198B1 (en) 2022-01-07 2022-12-19 Battery capacity prediction apparatus and operating method thereof
ES22919057T ES3055131T3 (en) 2022-01-07 2022-12-19 Battery capacity prediction apparatus and operating method thereof
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118777889A (zh) * 2024-09-11 2024-10-15 宁波德业储能科技有限公司 一种电池容量预测方法、预测装置及其相关设备

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20250073711A (ko) * 2023-11-20 2025-05-27 주식회사 엘지에너지솔루션 배터리 진단 장치 및 방법
KR20250153006A (ko) * 2024-04-17 2025-10-24 주식회사 엘지화학 배터리 수명 예측 장치 및 배터리 관리 방법
KR20260035578A (ko) * 2024-09-06 2026-03-13 주식회사 엘지에너지솔루션 배터리 진단 장치 및 그 방법

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20140056693A (ko) * 2012-10-31 2014-05-12 한국전기연구원 배터리 관리 시스템, 및 배터리 관리 시스템을 이용하는 배터리 충전상태의 추정방법
US20140333313A1 (en) * 2013-05-13 2014-11-13 Southwest Research Institute Application independent map-based cycle life testing of battery cells
KR20160067559A (ko) * 2014-12-04 2016-06-14 주식회사 엘지화학 배터리 사용 패턴 분석 장치 및 방법
KR20200140093A (ko) * 2019-06-05 2020-12-15 삼성에스디아이 주식회사 배터리의 충방전 사이클에 따른 용량 변화 예측방법 및 예측시스템
KR20220003018A (ko) 2019-04-30 2022-01-07 웨스팅하우스 일렉트릭 컴퍼니 엘엘씨 적층 제조된 지르코늄 합금의 개선된 내식성

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP6284824B2 (ja) * 2014-05-14 2018-02-28 日立オートモティブシステムズ株式会社 二次電池監視装置、二次電池劣化予測装置、および、二次電池の電池容量の予測方法
JP6380417B2 (ja) * 2016-01-21 2018-08-29 横河電機株式会社 二次電池容量測定システム及び二次電池容量測定方法
CN110462916B (zh) * 2017-03-31 2023-06-20 株式会社杰士汤浅国际 蓄电元件管理装置以及蓄电元件管理方法
TWI628453B (zh) * 2018-01-19 2018-07-01 新盛力科技股份有限公司 電池容量的預估方法
CN110068765B (zh) * 2018-01-19 2021-06-15 新盛力科技股份有限公司 电池容量的预估方法
US20200011932A1 (en) * 2018-07-05 2020-01-09 Nec Laboratories America, Inc. Battery capacity fading model using deep learning
TWI673507B (zh) * 2018-12-06 2019-10-01 新盛力科技股份有限公司 電池電量狀態的預估方法
US10921383B2 (en) * 2019-03-07 2021-02-16 Mitsubishi Electric Research Laboratories, Inc. Battery diagnostic system for estimating capacity degradation of batteries
KR102801609B1 (ko) * 2019-10-24 2025-04-25 주식회사 엘지에너지솔루션 배터리 퇴화도 진단 장치 및 방법
US11300626B2 (en) * 2020-01-15 2022-04-12 GM Global Technology Operations LLC Method and system for battery capacity estimation
CN113030760B (zh) * 2021-03-25 2023-02-03 昆山宝创新能源科技有限公司 电池寿命预测方法、设备及存储介质

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20140056693A (ko) * 2012-10-31 2014-05-12 한국전기연구원 배터리 관리 시스템, 및 배터리 관리 시스템을 이용하는 배터리 충전상태의 추정방법
US20140333313A1 (en) * 2013-05-13 2014-11-13 Southwest Research Institute Application independent map-based cycle life testing of battery cells
KR20160067559A (ko) * 2014-12-04 2016-06-14 주식회사 엘지화학 배터리 사용 패턴 분석 장치 및 방법
KR20220003018A (ko) 2019-04-30 2022-01-07 웨스팅하우스 일렉트릭 컴퍼니 엘엘씨 적층 제조된 지르코늄 합금의 개선된 내식성
KR20200140093A (ko) * 2019-06-05 2020-12-15 삼성에스디아이 주식회사 배터리의 충방전 사이클에 따른 용량 변화 예측방법 및 예측시스템

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
SCHIMPE MICHAEL, BARRERAS JORGE V., WU BILLY, OFFER GREGORY J.: "Battery Degradation-Aware Current Derating: An Effective Method to Prolong Lifetime and Ease Thermal Management", JOURNAL OF THE ELECTROCHEMICAL SOCIETY, ELECTROCHEMICAL SOCIETY., vol. 168, no. 6, 14 June 2021 (2021-06-14), pages 1 - 13, XP093021162, ISSN: 0013-4651, DOI: 10.1149/1945-7111/ac0553 *
See also references of EP4425198A4

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118777889A (zh) * 2024-09-11 2024-10-15 宁波德业储能科技有限公司 一种电池容量预测方法、预测装置及其相关设备

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