TY - GEN
T1 - State of Charge Estimation for Lithium-Ion Batteries Based on Informer-LSTM Hybrid Network
AU - Song, Ningfei
AU - Jin, Nanlin
AU - Wang, Jingchen
AU - Zhang, Jie
AU - Man, Ka Lok
AU - Smith, Jeremy S.
AU - Yue, Yutao
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Accurate State of Charge (SoC) estimation is essential for efficient battery management systems (BMS). In this study, we propose a novel hybrid neural network architecture, combining the Informer and Long Short-Term Memory (LSTM) networks. Our hybrid network captures temporal dependencies and nonlinear characteristics inherent in battery data, enhancing sequence integration capabilities and computational efficiency. Experimental results on battery datasets demonstrate the effectiveness of our approach, with the proposed method achieving a maximum Mean Absolute Error (MAE) of 1.395% and a maximum Root Mean Square Error (RMSE) of 1.593%. Our findings suggest that the Informer-LSTM hybrid network holds promise for improving battery SoC estimation accuracy and enhancing battery management systems.
AB - Accurate State of Charge (SoC) estimation is essential for efficient battery management systems (BMS). In this study, we propose a novel hybrid neural network architecture, combining the Informer and Long Short-Term Memory (LSTM) networks. Our hybrid network captures temporal dependencies and nonlinear characteristics inherent in battery data, enhancing sequence integration capabilities and computational efficiency. Experimental results on battery datasets demonstrate the effectiveness of our approach, with the proposed method achieving a maximum Mean Absolute Error (MAE) of 1.395% and a maximum Root Mean Square Error (RMSE) of 1.593%. Our findings suggest that the Informer-LSTM hybrid network holds promise for improving battery SoC estimation accuracy and enhancing battery management systems.
KW - battery management systems (BMS)
KW - Informer
KW - Long Short-Term Memory (LSTM) network
KW - State of Charge (SoC)
UR - http://www.scopus.com/inward/record.url?scp=85213374024&partnerID=8YFLogxK
U2 - 10.1109/ISOCC62682.2024.10762752
DO - 10.1109/ISOCC62682.2024.10762752
M3 - Conference Proceeding
AN - SCOPUS:85213374024
T3 - Proceedings - International SoC Design Conference 2024, ISOCC 2024
SP - 201
EP - 202
BT - Proceedings - International SoC Design Conference 2024, ISOCC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st International System-on-Chip Design Conference, ISOCC 2024
Y2 - 19 August 2024 through 22 August 2024
ER -
