• Title/Summary/Keyword: Battery Aging

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Battery Sizing of Lithium-Based Battery for Emergency Power Supply in Nuclear Power Plants (전 비상전원 적용을 위한 리튬계열전지 용량 설계)

  • Park, Seongyun;Kim, Gunwoo;Lee, Pyeongyeon;Kim, Jonghoon;Park, Sungbeak;Kim, Youngmi
    • The Transactions of the Korean Institute of Power Electronics
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    • v.24 no.5
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    • pp.342-348
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    • 2019
  • The emergency power supplies (EPSs) are required to increase battery sizing for protecting power source loss above designed criteria. This study proposes a sizing method for lithium-based batteries for EPSs in nuclear power plants on the basis of the calculation method for the required energy under variable conditions. The variable conditions are related with the characteristics of lithium-based batteries, such as the temperature of the location of EPS installation, aging, and design margin. The usage of lithium-based battery reduces the cost and installation space and enables the safe and long-term supply of power compared with the use of lead-acid battery.

Proposal Protection Algorithm of Dendritic Lithium for Battery Second Use ESS (재사용 ESS를 위한 리튬 배터리 덴드라이트 보호 알고리즘 제안)

  • Song, Jung-Yong;Huh, Chang-Su
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.31 no.6
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    • pp.422-426
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    • 2018
  • The lithium-ion battery pack of an electric vehicle (EV) deserves to be considered for an alternative use within smart-grid infrastructure. Despite the long automotive service life, EV batteries retain over 70~80% of their initial capacity. These battery packs must be managed for their reliability and safety. Therefore, a battery management system (BMS) should use specific algorithms to measure and estimate the status of the battery. Most importantly, the BMS of a grid-connected energy storage system (ESS) must ensure that the lithium-ion battery does not catch fire or explode due to an internal short from uncontrolled dendrite growth. In other words, the BMS of a lithium-ion battery pack should be capable of detecting the battery's status based on the electrochemical reaction continuously until the end of the battery's lifespan. In this paper, we propose a new protection algorithm for a dendritic lithium battery. The proposed algorithm has applied a parameter from battery pack aging results and has control power managing.

Machine Learning-based SOH Estimation Algorithm Using a Linear Regression Analysis (선형 회귀 분석법을 이용한 머신 러닝 기반의 SOH 추정 알고리즘)

  • Kang, Seung-Hyun;Noh, Tae-Won;Lee, Byoung-Kuk
    • The Transactions of the Korean Institute of Power Electronics
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    • v.26 no.4
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    • pp.241-248
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    • 2021
  • A battery state-of-health (SOH) estimation algorithm using a machine learning-based linear regression method is proposed for estimating battery aging. The proposed algorithm analyzes the change trend of the open-circuit voltage (OCV) curve, which is a parameter related to SOH. At this time, a section with high linearity of the SOH and OCV curves is selected and used for SOH estimation. The SOH of the aged battery is estimated according to the selected interval using a machine learning-based linear regression method. The performance of the proposed battery SOH estimation algorithm is verified through experiments and simulations using battery packs for electric vehicles.

Design and Development of a Public Waste Battery Diagnostic Device

  • Kim, Sang-Bum;Lee, Sang-Hyun
    • International Journal of Advanced Culture Technology
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    • v.10 no.3
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    • pp.281-286
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    • 2022
  • In this study, design of an intuitive internal resistance diagnostic device is to diagnose the residual capacity and aging of the battery regardless of the model and the internal protocol of the waste battery through the method of measuring the internal resistance of a waste battery. In this paper, charging and discharging were continuously performed with 2A charging and 5A discharging in order to secure data on impedance changes that may occur in the charging and discharging process of various methods. As a result of the final experiment, it was confirmed that the impedance change occurred during charging and discharging, and the amount of change increased as the charging/discharging C-rate increased. In addition, it was confirmed that the waste battery aged or abnormal cell had a large change in the impedance value.

Detection Algorithm and Extract of Deviation Parameters for Battery Pack Based on Internal Resistance Aging (저항 열화 기반의 배터리 팩 편차 파라미터 추출 방안 및 검출 알고리즘)

  • Song, Jung-Yong;Huh, Chang-Su
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.31 no.7
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    • pp.515-520
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    • 2018
  • A large number of lithium-ion batteries are arranged in series and parallel in battery packs, such as those in electric vehicles or energy storage systems. As battery packs age, their output power and energy density drop because of voltage deviation, constant and non-uniform exposure to abnormal environments, and increased contact resistance between batteries; this reduces application system efficiency. Despite the balancing circuit and logic of the battery management system, the output of the battery pack is concentrated in the most severely aged unit cell and the output is frequently limited by power derating. In this study, we implemented a cell imbalance detection algorithm and selected parameters to detect a sudden decrease in battery pack output. In addition, we propose a method to increase efficiency by applying the measured testing values considering the operating conditions and abnormal conditions of the battery pack.

Battery Internal Resistance Measurement System Robust to Charger Harmonic Noise (충전기 고조파 잡음에 강인한 배터리 내부저항 측정 시스템)

  • Lee, Hyung-Kyu;Kim, Gi-Taek
    • Journal of IKEEE
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    • v.24 no.4
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    • pp.1129-1135
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    • 2020
  • The effects of battery aging limit the rechargeable capacity, State of Health(SoH). It is very important to estimate the SoH in the battery monitoring system(BMS) and many algorithms of measuring the internal resistance of the battery were proposed. A method is used by applying a current source of a specific frequency to the battery and measuring the voltage response. When charging harmonic noise is generated in the voltage response, it results in poor resistance measurement accuracy. In this paper, a robust battery internal resistance measurement algorithm is proposed to eliminate the effect of charging noise by integrating the current source and voltage response signals for a certain period. It showed excellent accuracy and stable measurement results. Applying to the BMS for uninterruptible power supply, the usefulness of the proposed method is verified.

Performance improvement of SOC indicator for electric vehicle using hydrometer (온-라인 비중계를 이용한 전기자동차용 바테리 잔존용량계의 성능개선)

  • 박종건;임영철;박철수;류영재
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.423-426
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    • 1996
  • The conditions to be satisfied with SOC(State-of-Charge) indicator installed on the electric vehicle were that it should be used under frequent loading conditions and that it should enable the monitor to adjust to the aging effect. But, the state-of-charge test requires a lengthy stabilization period after discharge cycles and the ampere-hour test requires the knowledge of the battery capacity in terms of amp-hours. However, a monitoring technique combining the state-of-charge test to enable the monitor to adjust to the aging effect with the ampere-hour test to use under frequent loading condition is studied and implemented on a microcontroller-based circuit in this paper. Specially, optical fiber is used to realize hydrometer which is immune to electromagnetic interference and toxic environment and makes it possible to be used in a wide temperature range.

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State of Health estimation based on Secondary Li-ion battery Electrochemical Modeling and Electrical experiment (리튬 이차 전지의 전기화학 모델링과 전기적 실험 기반 상태 추정)

  • Kim, Su-An;Park, Seong-Yun;Kim, Jong-hoon
    • Journal of IKEEE
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    • v.24 no.4
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    • pp.1098-1103
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    • 2020
  • This paper deals with a method for estimating the battery state-of-health(SOH) through electrical experiments and electrochemical modeling of lithium-ion secondary battery. In order to confirm the actual battery SOH through the battery electrical aging experiment, the current integration method was used. The SOH is estimated using the internal resistance value derived from the electrical experiment. Also, in electrochemical modeling, the SOH is estimated through the change of the SEI layer with the increase of the number of cycles. The new SOH is derived by applying weighting factor to the three methods of estimating SOH, including the actual battery SOH.

Z-score Based Abnormal Detection for Stable Operation of the Series/Parallel-cell Configured Battery Pack (직병렬조합 배터리팩의 안전운용을 위한 Z-score 기반 이상 동작 검출 방법)

  • Kang, Deokhun;Lee, Pyeong-Yeon;Kim, Deokhan;Kim, Seung-Keun;Kim, Jonghoon
    • The Transactions of the Korean Institute of Power Electronics
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    • v.26 no.6
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    • pp.390-396
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    • 2021
  • Lithium-ion batteries have been designed and used as battery packs with series and parallel combinations that are suitable for use. However, due to its internal electrochemical properties, producing the battery's condition at the same value is impossible for individual cells. In addition, the management of characteristic deviations between individual cells is essential for the safe and efficient use of batteries as aging progresses with the use of batteries. In this work, we propose a method to manage deviation properties and detect abnormal behavior in the configuration of a combined battery pack of these multiple battery cells. The proposed method can separate and detect probabilistic low-frequency information according to statistical information based on Z-score. The verification of the proposed algorithm was validated using experimental results from 10S3P battery packs, and the implemented algorithm based on Z-score was validated as a way to effectively manage multiple individual cell information.

Battery State-of-Health Estimation Method based on Deep-learning and Feature Engineering (딥러닝과 특징 추출 기반 배터리 노화 상태 추정 방법)

  • Chang, Moon-Seok;Lee, Gang-Seok;Bae, Sungwoo
    • The Transactions of the Korean Institute of Power Electronics
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    • v.27 no.4
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    • pp.332-338
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    • 2022
  • This study proposes a battery state-of-health estimation method by applying a feature extraction technique. The technique that can improve estimation performance is the process of identifying and extracting meaningful data. To apply a data-driven-based aging state estimation method to batteries, health indicators are used as training data. However, limitations occur in extracting health indicators from charge/discharge cycles. This study proposes a deep-learning-based battery state-of-health estimation method that applies feature extraction techniques to compensate for this problem. According to the performance evaluation result of the proposed method, it has a low estimation error of 0.3887% based on an absolute error evaluation method.