A Parallel Self-Attention Transformer for Predicting the Remaining Useful Life of Lithium-Ion Batteries

• Published in: IEEE journal of emerging and selected topics in industrial electronics (Print) pp. 1 - 11
• Main Authors: Zhang, Shurong, Cui, Zhongrui, Zhang, Qin, Li, Yueyang
• Format: Journal Article
• Language: English
• Published: IEEE 08.07.2025
• Subjects: Batteries; Computer architecture; Data mining; Degradation; Encoding; Feature extraction; Forecasting; Lithium-ion battery; remaining useful life prediction; Time series analysis; time step variable block; transformer; Transformers; Vectors

Precisely forecasting the lifetime of lithium-ion batteries is crucial for addressing consumer worries regarding their safety and dependability. However, existing research predominantly focuses on individual degradation characteristics of batteries, neglecting their multiple degradation features or...