인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
A state of charge (SOC) estimation method based on coulomb counting requires an accurate initial SOC value to reset the accumulated errors during the integration process. However, accurate initial SOC estimation is challenging for lithium iron phosphate (LFP) batteries due to their flat SOC-OCV curve and hysteresis characteristics. To address these problems, this paper proposes an enhanced coulomb counting based SOC estimation algorithm that incorporates hysteresis characteristics. The hysteresis characteristics of the LFP battery are analyzed through major loop and minor loop experiments. In order to determine the accurate initial SOC value that matches the measured open circuit voltage (OCV) in the hysteresis characteristics of the battery, the proposed method creates a new SOC-OCV curve consisting of the average curves of the major loop and charge/discharge curves of minor loops. The operating point (SOC, OCV) of the battery is determined by linear interpolation after selecting a curve according to the previous SOC and the state of the battery. A test bench is constructed to verify the SOC estimation performance of the proposed method. As a result of the experiment, the proposed method has a smaller SOC estimation error by reflecting the hysteresis characteristics of SOC-OCV more accurately compared to the existing improved coulomb counting method. The mean squared error (MAE) and root mean squared error (RMSE) of the SOC estimation of the proposed method are both less than 0.5.
본문·목차
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UCI(KEPA) : I410-151-25-02-092320449
