1 citations · 2 across the 3 of their papers we have counts for
3 papers
eess.SY2025★ 1 cited
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★ 1 cited
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…
eess.SY2025
Debiasing Continuous-time Nonlinear Autoregressions
Simon Kuang, Xinfan Lin
We study how to identify a class of continuous-time nonlinear systems defined by an ordinary differential equation affine in the unknown parameter. We define a notion of asymptotic…