Journal of IKEEE (전기전자학회논문지)

Institute of Korean Electrical and Electronics Engineers (한국전기전자학회)
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Analysis of the Effect of Alternating Current Ripple on Electrical State of Health Degradation of 21700 Lithium-ion Battery

교류 리플이 21700 리튬 이온 배터리의 전기적 건강 상태 열화에 미치는 영향 분석

  • Bongwoo Kwak (Dept. of of Automotive Materials & Components R&D Group, Korea Institute of Industrial Technology)
  • Received : 2023.11.24
  • Accepted : 2023.12.13
  • Published : 2023.12.31
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Abstract

In this paper, the effect of AC ripple on the lifetime of lithium-ion batteries is experimentally analyzed. Bidirectional power conversion system(PCS) is used to increase the efficiency of energy storage systems (ESS). When connected to the grid, a current ripple with a frequency twice the grid frequency is applied to the battery due to its structure. Therefore, to analyze the effect of AC ripple on Li-ion battery aging, cycle life test are performed by applying charge/discharge profiles of DC current and DC+AC current ripple specifications. Based on the experimental results, direct current internal resistance (DCIR), incremental capacitance (IC), and surface temperature were analyzed. As a result, it is confirmed that AC ripple does not directly affect degradation and that battery degradation slows down after a certain cycle. These results can serve as a guideline for optimizing filters to reduce ripple on the battery side in applications where AC ripple occurs.

본 논문에서는 AC 리플이 리튬 이온 배터리의 수명에 미치는 영향을 실험적으로 분석한다. 에너지 저장 시스템(ESS)의 이용 효율을 높이기 위해 양방향 전력변환시스템(PCS)이 사용되며, 계통 연계 시 구조상 계통 주파수의 2배의 주파수를 갖는 전류 리플이 배터리에 인가되게 된다. 따라서, AC 리플이 Li-ion 배터리의 노화에 미치는 영향에 대해 분석하기 위해 DC 및 DC+AC 리플 사양의 충/방전 프로파일을 적용하여 노화 실험이 수행되었다. 실험 결과를 바탕으로 직류 내부 저항(DCIR), 증분 용량(IC), 표면 온도를 분석하였다. 결과적으로 AC 리플이 노화에 직접적으로 영향을 미치지 않으며 특정 주기 이 후 배터리 노화가 둔화되는 것을 확인하였다. 이러한 결과는 AC 리플이 발생하는 어플리케이션에서 전류 리플을 줄이기 위해 적용된 필터를 개선하는 데 도움이 될 수 있다.

Keywords

Acknowledgement

This study has been conducted with the support of the Korea Institute of Industrial Technology as "Development of core technologies of AI based self-power generation and charging for next-generation mobility (KITECH EH-23-0013)".

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