Yunseok Choi
UNIST 에너지화학공학과 · 공학
윤승욱 교수의 연구실은 리튬이온 배터리의 수명 예측 및 안정성 향상을 위한 지능형 예측 모델과 신소재 기반 배터리 시스템 개발에 중점을 두고 있습니다. 특히, 기계학습 기반 상태항력(SOH) 예측 기술과 해수 배터리, 물기반 소화 기술(Water-in-Battery)을 통한 안전성 향상 기술을 융합적으로 연구하고 있습니다. 또한, 고성능 열관리를 위한 메탈 폼 기반 열전달 기술도 함께 개발하여 전자기기의 지속가능성과 안정성을 제고하고자 합니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
To ensure smooth and reliable operations of battery systems, reliable prognosis with accurate prediction of State of Health of lithium ion batteries is of utmost importance. However, battery degradation is a complex challenge involving many electrochemical reactions at anode, separator, cathode and electrolyte/electrode interfaces. Also, there is significant effect of the operating conditions on the battery degradation. Various machine learning techniques have been applied to estimate the capaci
Accurately estimating the state-of-health (SOH) of lithium-ion batteries is emerging as a hot topic because of the rapid increase in electric appliance usage. However, versatile applicability to various battery compositions and diverse cycling conditions, and prediction only with partial data still remain challenges. In this paper, a Deep-learning-based Graphical approach to Estimation of Lithium-ion batteries SOH (D-GELS) was developed to predict the SOH covering three cathode materials, LiFePO
Rechargeable seawater batteries (SWBs) use Na + ions dissolved in water (seawater or salt-water) as the cathode material. They are attracting attention for marine applications such as light buoys, marine drones, auxiliary power for sailing boats and so on. So far, SWB design has been developed from the coin-type to prismatic-shape cell for research purposes to investigate cell components and electrochemical behaviors. However, for commercial applications, that generally require >12 V and >
The fire condition of lithium-ion batteries is satisfied by fulfilling three elements. Through the concept of Water-in-Battery (WiB), fire can be suppressed by controlling these elements via direct water penetration into the cell, reducing temperature and blocking oxygen.
Advancements in technology have led to electronics with higher power densities, which strains the sustainability of these devices. In this context, using metal foams in pool boiling can provide solutions by enhancing heat transfer. The porous structure of metal foams affects the boiling parameters such as critical heat flux (CHF) and boiling heat transfer coefficient (BHTC). To study these effects, copper foams of varying thicknesses and PPI were used, and they were attached to smooth silicon su
