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A Lithium-Ion Battery Remaining Useful Life Prediction Model Based on CEEMDAN Data Preprocessing and HSSA-LSTM-TCN

Shaoming Qiu,
Bo Zhang,
Yana Lv,
Jie Zhang and
Chao Zhang

World Electr. Veh. J.2024, 15(5), 177;https://doi.org/10.3390/wevj15050177

24 April 2024

Accurate prediction of the Remaining Useful Life (RUL) of lithium-ion batteries is crucial for reducing battery usage risks and ensuring the safe operation of systems. Addressing the impact of noise and capacity regeneration-induced nonlinear feature...

(This article belongs to the Special Issue Lithium-Ion Batteries for Electric Vehicle)

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A Lithium-Ion Battery Remaining Useful Life Prediction Model Based on CEEMDAN Data Preprocessing and HSSA-LSTM-TCN