Yang‐Ki Hong
Papers
1
Total Citations
11
H-Index
1
About
Yang‐Ki Hong is a leading researcher in electric motor drives and power electronics, with a focus on advancing the efficiency and reliability of interior permanent magnet (IPM) motors—key components in electric vehicles (EVs), robotics, and drones. His major contributions include pioneering neural network-based control strategies that integrate cloud-based training for real-time optimization of maximum torque per ampere (MTPA), flux-weakening (FW), and maximum torque per volt (MTPV) techniques. His most-cited work, a 2023 paper on this topic, has already garnered 11 citations, reflecting its immediate impact on the field. Hong’s research addresses critical challenges in EV drivetrains, enabling more efficient and robust motor control under varying operating conditions. His work is notable for bridging machine learning with classical motor control theory, offering scalable solutions for next-generation electric propulsion systems. With a strong publication record and growing citation influence, Hong continues to shape the future of sustainable transportation and automation technologies.
Research Focus
Key Achievements
Top Papers
- 1