FAN Guodong

FAN Guodong is an Associate Professor in the School of Mechanical Engineering at Shanghai Jiao Tong University. His research focuses on intelligent battery management systems, including modeling and control of battery systems. He has published extensively in journals such as Applied Energy, Journal of Power Sources, and Journal of Energy Storage, with works addressing battery capacity estimation, electrochemical modeling, and state-of-charge estimation. FAN has also contributed to the development of reduced-order electrochemical models and has been involved in various research projects related to battery performance and degradation analysis. His academic work is supported by his affiliation with the Institute of Intelligent Vehicle at the university.

Guodong Fan is a researcher at Shanghai Jiao Tong University specializing in lithium-ion batteries, electrochemistry, and state-of-charge (SOC)/state-of-health (SOH) estimation. His work focuses on developing reduced-order models and physics-based approaches for battery aging analysis and performance prediction. Fan's research includes advanced techniques for parameter identification, model order reduction, and thermal-coupled estimation methods. His publications explore the application of convolutional neural networks and fractional-order models for accurate state-of-energy estimation. Additionally, he investigates the impact of intermittent overcharging and internal heating on battery reliability and longevity, contributing to the development of optimal charging strategies for lithium-ion batteries.