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http://dx.doi.org/10.3795/KSME-A.2016.40.10.895

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

Kim, Dongjin (School of Aerospace and Mechanical Engineering, Korea Aerospace Univ.)
Kim, Seok Goo (School of Aerospace and Mechanical Engineering, Korea Aerospace Univ.)
Choi, Jooho (School of Aerospace and Mechanical Engineering, Korea Aerospace Univ.)
Song, Hwa Seob (Hyosung Corporation)
Park, Sang Hui (Hyosung Corporation)
Lee, Jaewook (School of Aerospace and Mechanical Engineering, Korea Aerospace Univ.)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.40, no.10, 2016 , pp. 895-900 More about this Journal
Abstract
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.
Keywords
Li-ion Battery; Battery Degradation Model; Parameter Estimation; Markov Chain Monte Carlo Method;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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