5 papers
Relative Discharge Stage (RDS) Classification: A Practical Indicator of Battery Discharge Progress
Khoa Tran, Tri Le, Hung-Cuong Trinh +1
Accurate remaining discharge time (RDT) prediction is challenging in real-world battery applications because future load profiles are unknown and highly dynamic. To address the unc…
Joint Remaining Useful Life Prediction and Capacity Estimation of Lithium-Ion Batteries Using Partial-Charging Data
Khoa Tran, Ho-Si-Hung Nguyen, Phone Wai Yan Moe +2
Joint remaining useful life (RUL) prediction and capacity estimation require representations of both gradual degradation and recent battery behavior. This paper presents a cross-ex…
C2L-Net: A Data-Driven Model for State-of-Charge Estimation of Lithium-Ion Batteries During Discharge
Khoa Tran, Tri Le, Nhu Nguyen Gia +4
Accurate state-of-charge (SOC) estimation is critical for the safe and efficient operation of lithium-ion batteries in battery management systems (BMS). Although data-driven approa…
SeqBattNet: A Discrete-State Physics-Informed Neural Network with Aging Adaptation for Battery Modeling
Khoa Tran, Hung-Cuong Trinh, Vy-Rin Nguyen +2
Accurate battery modeling is essential for reliable state estimation in modern applications, such as predicting the remaining discharge time and remaining discharge energy in batte…
HyBattNet: Hybrid Framework for Predicting the Remaining Useful Life of Lithium-Ion Batteries
Khoa Tran, Tri Le, Bao Huynh +4
Accurate prediction of the Remaining Useful Life (RUL) is essential for enabling timely maintenance of lithium-ion batteries, impacting the operational efficiency of electric appli…