Earticle

현재 위치 Home

Device or Module

A Study on Impedance Change Trend and Battery Life Analysis through Battery Performance Deterioration Factors

첫 페이지 보기
  • 발행기관
    국제인공지능학회(구 한국인터넷방송통신학회) 바로가기
  • 간행물
    International Journal of Internet, Broadcasting and Communication 바로가기
  • 통권
    Vol.15 No.3 (2023.08)바로가기
  • 페이지
    pp.129-134
  • 저자
    Mi-Jin Choi, Young-Jun Kim, Sang-Bum Kim
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A435275

※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

원문정보

초록

영어
Although the use of batteries is rapidly increasing worldwide to improve carbon neutrality and energy efficiency, performance degradation due to the increase in the number of uses is inevitable as it is a finite resource that can be applied according to capacity and specifications. Deterioration and failure of batteries are recognized as important problems in various applications using batteries, including electric vehicles. In order to solve these problems, a diagnostic technology capable of accurately predicting battery life and grasping state information is required, but it is difficult in a non-linear form due to internal structure or chemical change. In this paper, the factors that generally cause battery performance change are directly applied to check whether there are external changes and impedance changes in the battery, and to analyze whether they affect battery life. Impedance change trends and result values were confirmed using a universal impedance spectroscopy method and a self-developed internal impedance measurement method. The results did not significantly affect the impedance change trend. It was confirmed that the increase in the number of times of battery use was prominent in the impedance change trend.

목차

Abstract
1. Introduction
2. Design of Impedance
3. Test Configuration for Impedance Variation Factors
4. Test Conditions for Impedance Variation Factors
5. Test Results for Impedance Variation Factors.
Acknowledgement
References

키워드

Impedance electric vehicles Lithium-Ion Battery Variation Factor Prediction

저자

  • Mi-Jin Choi [ Break The Rule Co, Ltd., Gwangju, Korea ]
  • Young-Jun Kim [ Break The Rule Co, Ltd., Gwangju, Korea ]
  • Sang-Bum Kim [ Professor, Department of Electronic Engineering, Honam University, Gwangju, Korea ] Corresponding Author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    국제인공지능학회(구 한국인터넷방송통신학회) [The International Association for Artificial Intelligence]
  • 설립연도
    2000
  • 분야
    공학>전자/정보통신공학
  • 소개
    인터넷방송, 인터넷 TV , 방송 통신 네트워크 및 관련 분야에 대한 국내는 물론 국제적인 학술, 기술의 진흥발전에 공헌하고 지식 정보화 사회에 기여하고자 한다.

간행물

  • 간행물명
    International Journal of Internet, Broadcasting and Communication
  • 간기
    계간
  • pISSN
    2288-4920
  • eISSN
    2288-4939
  • 수록기간
    2009~2025
  • 십진분류
    KDC 326 DDC 380

이 권호 내 다른 논문 / International Journal of Internet, Broadcasting and Communication Vol.15 No.3

    피인용수 : 0(자료제공 : 네이버학술정보)

    함께 이용한 논문 이 논문을 다운로드한 분들이 이용한 다른 논문입니다.

      페이지 저장