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Remaining Useful Life Estimation of Li-ion Battery for Energy Storage System Using Markov Chain Monte Carlo Method
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마코프체인 몬테카를로 방법을 이용한 에너지 저장 장치용 배터리의 잔존 수명 추정

논문 기본 정보

Type
Academic journal
Author
Dongjin Kim (한국항공대학교) Seok Goo Kim (한국항공대학교) Jooho Choi (한국항공대학교) Hwa Seob Song (효성중공업) Sang Hui Park (효성중공업) Jaewook Lee (한국항공대학교)
Journal
The Korean Society of Mechanical Engineers Transactions of the Korean Society of Mechanical Engineers - A Vol.40 No.10 (Wn.373) KCI Accredited Journals SCOPUS
Published
2016.10
Pages
895 - 900 (6page)

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Remaining Useful Life Estimation of Li-ion Battery for Energy Storage System Using Markov Chain Monte Carlo Method
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Abstract· Keywords

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Remaining useful life (RUL) estimation of the Li-ion battery has gained great interest because it is necessary for quality assurance, operation planning, and determination of the exchange period. This paper presents the RUL estimation of an Li-ion battery for an energy storage system using exponential function for the degradation model and Markov Chain Monte Carlo (MCMC) approach for parameter estimation. The MCMC approach is dependent upon information such as model initial parameters and input setting parameters which highly affect the estimation result. To overcome this difficulty, this paper offers a guideline for model initial parameters based on the regression result, and MCMC input parameters derived by comparisons with a thorough search of theoretical results.
#Li-ion Battery(리튬이온 배터리) #Battery Degradation Model(배터리 열화 모델) #Parameter Estimation(파라미터 추정) #Markov Chain Monte Carlo Method (MCMC방법론)

Contents

초록
Abstract
1. 서론
2. MCMC를 이용한 배터리의 잔존 수명 추정
3. 에너지 저장장치용 배터리 잔존 수명 추정법 적용
4. MCMC 초기 값 및 설정 값 결정
5. 결론
참고문헌(References)

References (11)

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[학술지(정기간행물)] - 서보환 / 2012 / Condition Monitoring of Lithium Polymer Batteries Based on a Sigma-Point Kalman Filter / Journal of Power Electronics 12 (5) : 778 ~ 786 google schola [학술지(정기간행물)] - Bhangu, B. S. / 2005 / Nonlinear Observers for Predicting State-of-Charge and State-of-Health of Lead-Acid Batteries for Hybrid-Electric Vehicles / IEEE Transactions on Vehicular Technology 54 (3) : 784 ~ 794 google schola [학술지(정기간행물)] - Andre, D. / 2013 / Comparative Study of a Structured Neural Network and an Extended Kalman Filter for State of Health Determination of Lithium-ion Batteries in Hybrid Electric Vehicles / Engineering Applications of Artificial Intelligence 26 (3) : 951 ~ 961 google schola [학술지(정기간행물)] - Dalal, M. / 2011 / Lithium-ion Battery Life Prognostic Health Management System Using Particle Filtering Framework / Journal of Risk and Reliability 225 (1) : 81 ~ 90 google schola [학술지(정기간행물)] - Nuhic, A. / 2013 / Health Diagnosis and Remaining Useful Life Prognostics of Lithium-ion Batteries Using Data-driven Methods / Journal of Power Sources 239 : 680 ~ 688 google schola

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