5 papers
Rapid and robust parameter estimation for electrochemical battery models via BOLT: A batch-optimized local-to-global technique
Feng Guo, Luis D. Couto, Keivan Haghverdi +2
Accurate and efficient parameter estimation is essential for applying electrochemical battery models in simulation, state estimation, control, and repeated model updating. However,…
Physics-guided residual Kalman learning for state-of-charge estimation of lithium iron phosphate batteries
Feng Guo, Luis D. Couto, Khiem Trad +3
Accurate state of charge (SOC) estimation of lithium iron phosphate (LFP) batteries remains challenging because of their flat open-circuit-voltage (OCV)-SOC characteristics, temper…
Stability-Guaranteed Dual Kalman Filtering for Electrochemical Battery State Estimation
Feng Guo, Guangdi Hu, Keyi Liao +5
Accurate and stable state estimation is critical for battery management. Although dual Kalman filtering can jointly estimate states and parameters, the strong coupling between filt…
Residual Bias Compensation Filter for Physics-Based SOC Estimation in Lithium Iron Phosphate Batteries
Feng Guo, Luis D. Couto, Khiem Trad +2
This paper addresses state of charge (SOC) estimation for lithium iron phosphate (LFP) batteries, where the relatively flat open-circuit voltage (OCV-SOC) characteristic reduces ob…
Identifiability Analysis of a Pseudo-Two-Dimensional Model & Single Particle Model-Aided Parameter Estimation
L. D. Couto, K. Haghverdi, F. Guo +2
This contribution presents a parameter identification methodology for the accurate and fast estimation of model parameters in a pseudo-two-dimensional (P2D) battery model. The meth…