FWO Senior Postdoctoral Fellow · IEEE Senior Member
Electrochemical Models for Reliable, Intelligent Battery Control
I build physics-informed estimation, diagnosis, and control methods that connect high-fidelity battery models with deployable battery management systems.
I am an FWO Senior Postdoctoral Fellow and IEEE Senior Member, working jointly with VITO and UHasselt in Belgium. My research focuses on control-oriented electrochemical battery modelling, state estimation, parameter identification, safety, fault-tolerant control, and physics-guided AI for battery management systems.
The common thread across my work is deployment: methods should be physically meaningful, computationally efficient, and robust enough to support real battery systems across temperatures, operating profiles, and sensor uncertainty.
Research Interests
Control-oriented electrochemical battery modelling
Efficient SPM/P2D simplification, parameter grouping, thermal coupling, and state-space implementations for control and BMS use.
Battery state estimation and parameter identification
Robust SOC estimation, Kalman filtering, observer design, and operating-profile-aware electrochemical parameter estimation.
Battery safety, fault diagnosis, and fault-tolerant control
Sensor-fault diagnosis, safety-aware estimation, and fault-tolerant control methods for reliable battery operation.
Physics-guided AI for battery management systems
Hybrid physics-learning models that preserve interpretability while improving robustness under real operating conditions.
Collaboration
I welcome collaboration on electrochemical model reduction, battery state estimation, physics-informed machine learning, fault-tolerant control, and open-source tools for battery research.
feng.guo@vito.be