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논문 기본 정보

자료유형
학술대회자료
저자정보
Youngbin Song (Pohang University of Science and Technology) Minhwan Seo (Pohang University of Science and Technology) Shina Park (Pohang University of Science and Technology) Sang W. Kim (Pohang University of Science and Technology)
저널정보
제어로봇시스템학회 제어로봇시스템학회 국제학술대회 논문집 ICCAS 2021
발행연도
2021.10
수록면
462 - 467 (6page)

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초록· 키워드

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Initial parameter variances between cells in battery packs occur in a manufacturing process. Furthermore, this difference is intensified as the pack is being used, resulting in differences in capacity and the state of charge (SOC) between cells. Cell inconsistencies decrease the energy efficiency, and low-capacity cells in packs can occur an internal short circuit (ISC) fault which causes a thermal runaway in severe cases. However, the ISC may be misdiagnosed as cell inconsistencies and vice versa because the impacts of cell inconsistencies and the ISC are similar in particular charge/discharge. In this paper, a model-based cell inconsistency classification method is proposed. The equivalent circuit model of the fresh cell is used as a reference model, making it possible to save efforts in constructing parameter look-up tables for various degrees of aging. In addition, we use the SOC difference feature that can clearly distinguish the effects of inconsistencies and ISC using the reference SOC calculated by the nominal capacity. The proposed method was verified in simulation for various types and degrees of cell inconsistencies and ISC, and accurately identified inconsistent cells and ISC cells, thereby leading to efficient energy use and early detection of the ISC fault.

목차

Abstract
1. INTRODUCTION
2. MODEL-BASED FEATURE EXTRACTION
3. CELL INCONSISTENCY CLASSIFICATION
4. SIMULATION
5. RESULTS AND DISCUSSIONS
6. CONCLUSIONS
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