Korea Advanced Institute of Science and Technology · 工学
Professor Jaewook Lee's research lab specializes in advanced control systems and machine learning for energy storage systems, with a strong focus on the reliability and longevity of lithium-ion batteries (LIBs). The lab develops innovative control algorithms—such as iterative learning control and sliding mode control—for precision tracking and robustness under uncertainty, particularly in automation and robotic systems. It also pioneers data-driven approaches to predict battery degradation by extracting intra- and inter-cycle features from real-world-like cycling data, including rapid fade events and EV-relevant charge-discharge profiles. The lab integrates experimental validation with computational modeling to enhance the safety, performance, and lifespan prediction of batteries in electric vehicle applications.
Figures are computed from collected data and may differ slightly.
Daylighting metrics are used to predict the daylight availability within a building and assess the performance of a fenestration solution. In this process, building design parameters are inseparable from these metrics; therefore, we need to know which parameters are truly important and how they impact performance. The purpose of this study is to explore the relationship between building design attributes and existing daylighting metrics based on a new methodology we are proposing. This methodolo
Prediction of construction cost and life-cycle cost through preliminary estimate is very important for the economic decision-making in the early phase of building projects. However, the conventional preliminary estimate has a high error range and low reliability because it relies only on the basic information of projects. In addition, the consideration of the life-cycle cost of the building is insufficient, causing problems such as budget shortage, inaccurate budgeting, and life-cycle cost incre
This paper presents structural topology optimization applied to the coupled magneto-structural problem. The design goals are to minimize mechanical compliance and to maximize total magnetic force. To calculate the compliance and magnetic force, coupled magneto-structural analysis is performed using the finite-element method. From the solution of a magnetostatic analysis, distribution of the magnetic body force is obtained using the virtual air gap scheme. The structural analysis from the calcula
This paper presents structural topology optimization of an electro/permanent magnet linear actuator. The optimization goal is to maximize the average magnetic force acting on a plunger that travels over a distance of 20 mm. To achieve this goal, the magnetic field sources (i.e., permanent magnet, positive and negative direction coils), and ferromagnetic material of the yoke are simultaneously co-designed using four design variables for each finite element. The magnetic force is calculated using
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