A flexible RUL prediction method based on poly-cell LSTM with applications to lithium battery data

Jiaolong Wang, Fode Zhang, Jianchuan Zhang, Wen Liu, Kuang Zhou

Abstract: Highlights•The proposed PCLSTM uses degradation information more effectively.•The PCLSTM eases the computational burden.•The proposed PCLSTM is equipped with flexibility and robustness.•The effectiveness of the proposed method is illustrated by analyzing the lithium battery data.