most citedPhysics-guided residual Kalman learning for state-of-charge estimation of lithium iron phosphate batteries

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

eess.SY2026

When voltage sensors fail: Electrochemically constrained fault-tolerant state estimation for flat-plateau LFP batteries

Feng Guo, Luis D. Couto, Hamid Hamed +5

The flat voltage plateau of lithium iron phosphate (LFP)/graphite cells makes electrochemical-state errors and voltage-measurement abnormalities produce similar innovations, compli…

eess.SY2026★ 1 cited

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…

eess.SY2025

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…

eess.SY2025

Residual Bias Compensation Dual Extended Kalman 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…

eess.SY2025

Adaptive Dead-Zone Dual Sliding Mode Observer for Reliable Electrochemical Model-Based SOC Estimation

Guangdi Hu, Keyi Liao, Jian Ye +1

Accurate state-of-charge (SOC) estimation is essential for safe and efficient lithium-ion battery operation. Electrochemical models provide physically grounded SOC estimates, but n…