3 papers
eess.SY2026
Accelerating Bayesian Optimization for Nonlinear State-Space System Identification with Application to Lithium-Ion Batteries
Hao Tu, Jackson Fogelquist, Iman Askari +4
This paper studies system identification for nonlinear state-space models, a problem that arises across many fields yet remains challenging in practice. Focusing on maximum likelih…
eess.SY2025
Joint Parameterization of Hybrid Physics-Based and Machine Learning Li-Ion Battery Model
Jackson Fogelquist, Xinfan Lin
Electrochemical hybrid battery models have major potential to enable advanced physics-based control, diagnostic, and prognostic features for next-generation lithium-ion battery man…
eess.SY2025
Robust Estimation of Battery State of Health Using Reference Voltage Trajectory
Rui Huang, Jackson Fogelquist, Xinfan Lin
Accurate estimation of state of health (SOH) is critical for battery applications. Current model-based SOH estimation methods typically rely on low C-rate constant current tests to…