Seunghun Jang
Seunghun Jang / μž₯μŠΉν›ˆ
Ph.D. Student
shjang7071@kaist.ac.kr
0009-0006-1091-3200
Google Scholar
GitHub
12893948

Description

Seunghun Jang received his B.S. degree in the Department of Bio-Industrial Machinery Engineering from Pusan National University in 2021. He joined the MIC Lab in 2022 and went on to obtain the M.S. degree in the Department of Mechanical Engineering from Gwangju Institute of Science and Technology (GIST) in 2024. He is currently pursuing a Ph.D at the Cho Chun Shik Graduate School of Mobility at the KAIST, where he continues his research in the MIC Lab.

His current research interests include state estimation of Synchronous Machines (SMs), physics-informed online learning of SMs, optimal control of electric drives.

Publications in MIC Lab


Quick Links


International Conference Papers


    2025
  1. Physics-Informed Online Learning of Flux Linkage Model for Synchronous Machine
    Seunghun Jang, Myeongseok Ryu, Kyunghwan Choi*
    IEEE IECON(accepted, in press), 2025 [🌐 Preprint] [πŸ“ƒ Full-Text] [GitHub logo Code]

    2. 2024
  2. Neural Network-based Nonlinearity Estimation of Voltage Source Inverter for Synchronous Machine Drives
    Yeongho Jeong, Seunghun Jang, Kyunghwan Choi*
    IEEE International Symposium on Industrial Electronics (ISIE), pp. 1-5, 2024 [🌐 Online] [GitHub logo Code]
  3. Extended State Observer Based Stator Flux Linkage Estimation of Nonlinear Synchronous Machines
    Seunghun Jang, Bernd Pfeifer, Christoph M. Hackl, Kyunghwan Choi*
    IEEE International Symposium on Industrial Electronics (ISIE), pp. 1-5, 2024 [🌐 Online] [πŸ“ƒ Full-Text] [GitHub logo Code]

    4. 2023
  4. Stator Flux Linkage Estimation of Synchronous Machines Based on Integration Error Estimation for Improved Transient Performance
    Seunghun Jang, Kyunghwan Choi*
    IEEE Conference on Decision and Control (CDC), pp. 4197-4202, 2023 [🌐 Online] [πŸ“ƒ Full-Text] [GitHub logo Code]

Domestic Conference Papers


    2025
  1. Physics-Informed Online Learning for Stator Flux Linkage Estimation in Synchronous Machines
    λ™κΈ°μ „λ™κΈ°μ˜ μ‹€μ‹œκ°„ κ³ μ •μž μ‡„κ΅μžμ† 좔정을 μœ„ν•œ λ¬Όλ¦¬μ •λ³΄κΈ°λ°˜ ν•™μŠ΅
    Seunghun Jang, Kyunghwan Choi*
    μ œμ–΄λ‘œλ΄‡μ‹œμŠ€ν…œν•™νšŒ (ICROS), 2025 [πŸ“ƒ Full-Text]

    2. 2024
  2. Stator Flux Linkage Estimation of Nonlinear Synchronous Machines Based on the State Observer
    μƒνƒœ κ΄€μΈ‘κΈ° 기반 λΉ„μ„ ν˜• λ™κΈ°κΈ°μ˜ κ³ μ •μž μ‡„κ΅μžμ† μΆ”μ •
    Seunghun Jang, Kyunghwan Choi*
    μ œμ–΄λ‘œλ΄‡μ‹œμŠ€ν…œν•™νšŒ (ICROS), pp. 308-309, 2024 [🌐 DBpia Online] [πŸ“ƒ Full-Text]

    3. 2023
  3. Sator Flux Linkage Estimation Method of Synchronous Machines Based on Integration Error Estimation
    적뢄 였차 μΆ”μ • 기반 동기 μ „λ™κΈ°μ˜ 쇄ꡐ μžμ† μΆ”μ • 기법
    Seunghun Jang, Kyunghwan Choi*
    μ œμ–΄λ‘œλ΄‡μ‹œμŠ€ν…œν•™νšŒ (ICROS), pp. 177-178, 2023 [🌐 DBpia Online] [πŸ“ƒ Full-Text]

Master's Theses


    2024
  1. Online Stator Flux Linkage Estimation of Synchronous Machines
    Seunghun Jang, Kyunghwan Choi*
    Gwangju Institute of Science and Technology (GIST) Library, 2024 [πŸ“ƒ Full-Text]