Lithium-ion battery RUL prediction using CNN-BiLSTM-Attention
A hybrid prediction framework integrating convolutional neural networks (CNN), bidirectional long short-term memory networks (BiLSTM), attention mechanisms, and ensemble learning strategies is developed to improve prediction accuracy and robustness in lithium-ion battery remaining useful life prediction.