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Micro/nanoscale phase-change physics  

   > Two-phase closed thermosyphon

Intelligent thermal management 

Nanoengineered thermal materials

Renewable thermal energy solutions

ANN-based inverter cooling optimization

As the demand for high-performance electric vehicles (EVs) increases, the importance of energy-efficient thermal management of inverters has become ever more important. Also, the energy density, layout, and total power output of inverter chips have been rapidly changing. To address these evolving challenges and develop optimal thermal management solutions, we have incorporated an Artificial Neural Network (ANN)-based fast optimization scheme. This approach enables us to tackle the thermal issues across various industrial platforms, both by drastically reducing the time required for design optimization and by maximizing performance.

Multiscale Energy Laboratory

​Department of Mechanical Engineering ㅣ Korea Advanced Institute of Science and Technology, 291, Daehak-ro, Yuseong-gu, Daejeon, South Korea ㅣ Email: ysnam1@kaist.ac.kr

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