Dongmin Kim – Transportation Engineering – Best Researcher Award

Dongmin Kim - Transportation Engineering - Best Researcher Award

Post-doctoral researcher | Korea Advanced Institute of Science and Technology | South Korea

Dongmin Kim’s research field focuses on advancing the efficiency, reliability, and sustainability of electric vehicles through a multidisciplinary approach that integrates energy modeling, traffic analysis, and intelligent systems. His work emphasizes electric vehicle energy consumption modeling, auxiliary energy consumption, and battery aging, with a particular interest in developing battery-in-the-loop systems that simulate real-world driving environments for more accurate performance testing. A key part of his research investigates internal resistance degradation in lithium-ion batteries, analyzing how driving characteristics influence long-term battery health. Kim also explores cooperative-intelligent transport systems (C-ITS) and probe vehicle data to study macroscopic traffic patterns and their impact on driving efficiency, highlighting the interaction between vehicle technology and traffic flow. He has contributed to the development of real-time energy consumption estimation models, predictive frameworks for auxiliary energy use, and risk detection methods in connected transport systems. His publications cover a range of topics, from linear mixed-effects models for energy prediction to unsupervised learning approaches for identifying risky driving behaviors, demonstrating his integration of data science with mobility research. Additionally, Kim’s work extends into simulation-based studies of driving efficiency indexes and traffic signal control strategies optimized for electric vehicles, showcasing his interest in bridging battery science with intelligent transportation. Through conference presentations, patents, and invited talks, he has shared advancements in battery state management, charging infrastructure systems, and simulation tools that connect vehicle behavior with traffic conditions. His research not only deepens the understanding of battery performance under dynamic environments but also proposes innovative solutions for enhancing energy efficiency, extending battery lifecycles, and improving safety in future electric mobility ecosystems. This comprehensive approach positions Dongmin Kim at the intersection of mechanical engineering, transportation systems, and sustainable mobility innovation.

Profile: ORCID | Research Gate
Featured Publications:

Kim, D., Lee, H., & Lee, J. (2025). Unsupervised learning approach for risky driving behavior identification on expressways in C-ITS environments. IEEE Transactions on Intelligent Transportation Systems. Advance online publication.

Kim, D., Yun, J., Jang, K., & Woo, S. (2025, December). Auxiliary energy consumption of electric vehicles: Modeling and prediction using real-world vehicle data. Applied Energy. Advance online publication.

Kim, D., & Jang, K. (2025, September). Component-level analysis for developing an energy consumption model for battery electric vehicles (BEVs) in operation. eTransportation. Advance online publication.