연구처

배터리 응용 기술 연구 랩

Lab for Battery Applicaiton Technology

본 연구실은 배터리의 사용 중 안전한 관리 및 사용 후 경제적인 자원 재활용을 위한 가치 판단 기준 수립에 관한 배터리 응용 기술 연구를 주제로 다루고 있습니다.
구체적으로는 리튬 이온 배터리의 진단 및 예측 연구, 모듈·팩 시스템 응용 연구에 집중하고 있습니다.
배터리 진단 및 예측 연구 분야에서는 전지의 열화 메커니즘 이해를 바탕으로 내부 상태를 규명하고 이를 대표하는 건강 지표를 정량화하여 진단하는 기술, 잔존 수명 예측을 통한 안전한 배터리 관리 및 최적의 재활용 시점 판단 기술을 연구합니다.
더 나아가, 배터리 시스템 응용 연구 분야는 셀 단위에서 확장된 배터리 모듈·팩 내부의 불균일 현상 분석, ESS 또는 EV 탑재 배터리의 고도화된 실시간·온라인 분석 기술을 연구합니다.
최종적으로, 향후의 배터리 기반 서비스 사업(Battery as a Service, BaaS)에 기여할 배터리 생애 주기 간 포괄적 배터리 운영 관리 플랫폼 구축을 목표로 합니다.
This lab deals with battery application technology research on the establishment of valuation criteria for safe management of batteries and economical reuse/recycle of used battery.
Specifically, we are focusing on research for lithium-ion battery diagnosis and prognosis, research for application to battery pack systems.
From the field of battery diagnosis and prognosis research, we are studying the technology to identify the battery internal state based on the understanding of the degradation mechanisms and diagnose the battery using quantified health indicator (HI) that can represent the internal state, and the technology for safe battery management as well as economical allocation of reuse/recycle resources at the right time through remaining useful life (RUL) prediction.
In addition, the battery system application research area deals with the analysis of the heterogeneous distribution in the extended battery pack and the techniques for real-time, online analysis of onboard battery in ESS or EV.
Finally, we aim to develop a comprehensive battery operation & management platform which can play an important role in the Battery as a Service (BAAS) business.

This lab deals with battery application technology research on the establishment of valuation criteria for safe management of batteries and economical reuse/recycle of used battery.
Specifically, we are focusing on research for lithium-ion battery diagnosis and prognosis, research for application to battery pack systems.
From the field of battery diagnosis and prognosis research, we are studying the technology to identify the battery internal state based on the understanding of the degradation mechanisms and diagnose the battery using quantified health indicator (HI) that can represent the internal state, and the technology for safe battery management as well as economical allocation of reuse/recycle resources at the right time through remaining useful life (RUL) prediction.
In addition, the battery system application research area deals with the analysis of the heterogeneous distribution in the extended battery pack and the techniques for real-time, online analysis of onboard battery in ESS or EV.
Finally, we aim to develop a comprehensive battery operation & management platform which can play an important role in the Battery as a Service (BAAS) business.