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논문 기본 정보

자료유형
학술저널
저자정보
Changhao Piao (Chongqing University of Posts and Telecommunications) Zuncheng Li (Chongqing University of Posts and Telecommunications) Sheng Lu (Chongqing University of Posts and Telecommunications) Zhekui Jin (Chongqing University of Posts and Telecommunications) Chongdu Cho (Inha University)
저널정보
전력전자학회 JOURNAL OF POWER ELECTRONICS JOURNAL OF POWER ELECTRONICS Vol.16 No.1
발행연도
2016.1
수록면
217 - 226 (10page)

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초록· 키워드

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A new method is proposed based on a hidden Markov model (HMM) to estimate and analyze battery states of health. Battery system health states are defined according to the relationship between internal resistance and lifetime of cells. The source data (terminal voltages and currents) can be obtained from vehicular battery models. A characteristic value extraction method is proposed for HMM. A recognition framework and testing datasets are built to test the estimation rates of different states. Test results show that the estimation rates achieved based on this method are above 90% under single conditions. The method achieves the same results under hybrid conditions. We can also use the HMMs that correspond to hybrid conditions to estimate the states under a single condition. Therefore, this method can achieve the purpose of the study in estimating battery life states. Only voltage and current are used in this method, thereby establishing its simplicity compared with other methods. The batteries can also be tested online, and the method can be used for online prediction.

목차

Abstract
I. INTRODUCTION
II. HIDDEN MARKOV MODEL
III. DATA ANALYSIS
IV. HMM-BASED ESTIMATION
V. EXPERIMENTS
VI. CONCLUSION
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UCI(KEPA) : I410-ECN-0101-2016-560-002315362