한국통신학회논문지 (The Journal of Korean Institute of Communications and Information Sciences)

  • 제42권4호
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  • Pages.939-949
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  • 2017
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  • 1226-4717(pISSN)
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  • 2287-3880(eISSN)
한국통신학회 (The Korean Institute of Commucations and Information Sciences)
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배터리 잔존 유효 수명 예측을 위한 전기화학 모델 기반 고장 예지 및 건전성 관리 기술

Prognostics and Health Management for Battery Remaining Useful Life Prediction Based on Electrochemistry Model: A Tutorial

  • Choi, Yohwan (Sogang University Department of Electronic Engineering) ;
  • Kim, Hongseok (Sogang University Department of Electronic Engineering)
  • 투고 : 2017.02.16
  • 심사 : 2017.04.10
  • 발행 : 2017.04.30
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초록

고장 예지 및 건전성 관리 기술(Prognostics and Health Management; PHM)은 시스템의 현재 상태를 진단하고 향후 발생 가능한 고장 시점을 신뢰성 있게 예지하는 기술로써 유지 보수 비용의 절감 및 시스템의 안정성 향상을 꾀하고자 하는 다양한 산업분야에서 활발하게 이용되고 있다. 스마트 그리드의 에너지 저장장치, 전기차, 스마트폰, 항공우주산업 등 광범위한 사용처에서 중요한 에너지원으로 사용되고 있는 배터리 또한 성능 저하 및 폭발의 위험성으로부터 자유로울 수 없기 때문에 이러한 고장 예지 및 건전성 관리 기술이 반드시 적용되어야 할 어플리케이션이다. 본 논문에서는 PHM의 기본적인 개념을 소개함과 동시에 배터리의 잔존 유효 수명(Remaining Useful Life; RUL)을 예측하는 각종 알고리즘 및 성능 평가 지표 서술에 초점을 맞추도록 한다. 더불어 배터리의 기능적 동작 원리 및 전기화학 기반의 모델링에 대한 설명을 통해 향후 잠재적인 가능성을 지닌 배터리의 전반적인 특성에 대한 깊은 이해 및 응용 기술에 대한 통찰력을 제시하고자 한다.

Prognostics and health management(PHM) is actively utilized by industry as an essential technology focusing on accurately monitoring the health state of a system and predicting the remaining useful life(RUL). An effective PHM is expected to reduce maintenance costs as well as improve safety of system by preventing failure in advance. With these advantages, PHM can be applied to the battery system which is a core element to provide electricity for devices with mobility, since battery faults could lead to operational downtime, performance degradation, and even catastrophic loss of human life by unexpected explosion due to non-linear characteristics of battery. In this paper we mainly review a recent progress on various models for predicting RUL of battery with high accuracy satisfying the given confidence interval level. Moreover, performance evaluation metrics for battery prognostics are presented in detail to show the strength of these metrics compared to the traditional ones used in the existing forecasting applications.

키워드

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피인용 문헌

  1. 실시간 감시를 통한 교통신호제어기의 열화 감지 vol.18, pp.2, 2017, https://doi.org/10.33162/jar.2018.06.18.2.153
  2. Real-Time Prediction of Capacity Fade and Remaining Useful Life of Lithium-Ion Batteries Based on Charge/Discharge Characteristics vol.10, pp.7, 2017, https://doi.org/10.3390/electronics10070846