Journal of IKEEE (전기전자학회논문지)

Institute of Korean Electrical and Electronics Engineers (한국전기전자학회)
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State of Health estimation based on Secondary Li-ion battery Electrochemical Modeling and Electrical experiment

리튬 이차 전지의 전기화학 모델링과 전기적 실험 기반 상태 추정

  • Kim, Su-An (Dept. of Electrical Engineering, Chungnam National University) ;
  • Park, Seong-Yun (Dept. of Electrical Engineering, Chungnam National University) ;
  • Kim, Jong-hoon (Dept. of Electrical Engineering, Chungnam National University)
  • Received : 2020.11.25
  • Accepted : 2020.12.30
  • Published : 2020.12.31
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Abstract

This paper deals with a method for estimating the battery state-of-health(SOH) through electrical experiments and electrochemical modeling of lithium-ion secondary battery. In order to confirm the actual battery SOH through the battery electrical aging experiment, the current integration method was used. The SOH is estimated using the internal resistance value derived from the electrical experiment. Also, in electrochemical modeling, the SOH is estimated through the change of the SEI layer with the increase of the number of cycles. The new SOH is derived by applying weighting factor to the three methods of estimating SOH, including the actual battery SOH.

본 논문은 리튬 이온 이차 전지의 전기적 실험 및 전기화학적 모델링을 통한 배터리 수명 상태(SOH)의 추정 방법을 다룬다. 배터리 전기적 노화 실험을 통하여 실제 배터리 수명 상태를 확인하기 위하여 전류 적산법을 사용한다. 전기적 실험에서 도출한 내부저항 값을 사용하여 SOH를 추정하며, 전기화학 모델링에서 사이클 수의 증가에 따른 SEI Layer의 변화를 통해 SOH를 추정한다. 실제 배터리 수명 상태를 포함한 세 가지 방법의 SOH 추정 방법에 가중치를 적용하여 새로운 SOH를 도출하며, 이는 전류적산법을 사용하여 구한 실제 값과의 오차를 줄여주어 추정 성능을 높인다.

Keywords

Acknowledgement

This research was supported by the projects of the Korea Electric Power Corporation (R19XO01-45) and the Technology Innovation Program(No. 20011626) funded by the Ministry of Trade, Industry & Energy(MOTIE, Korea).

References

  1. Agency, "I. E. World Energy Outlook 2012. Paris," International energy agency.
  2. A. Zenati et al., "A Methodology to Assess the State Of Health of Lithium-ion Batteries Based on the Battery's Parameters and a Fuzzy Logic System." IECON 2010, 2010.
  3. Bak, T., & Lee, S. "Accurate Estimation of Battery SOH and RUL Based on a Progressive LSTM with a Time Compensated Entropy Index," Annual Conference of the PHM Society, Vol.11, No.1. 2019. DOI: 10.36001/phmconf.2019.v11i1.833