Indirect Prediction of Lithium-Ion Battery RUL Based on CEEMDAN and CNN-BiGRU

• Published in: Energies (Basel) Vol. 17; no. 7; p. 1704
• Main Authors: Lv, Kai, Ma, Zhiqiang, Bao, Caijilahu, Liu, Guangchen
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2024
• Subjects: Accuracy; Aging; Algorithms; Analysis; Batteries; bidirectional gate recurrent unit network; capacity regeneration; complete ensemble empirical mode decomposition with adaptive noise; Datasets; Lithium; lithium-ion battery; Methods; Neural networks; remaining useful life; Time series; Trends

Predicting the remaining useful life (RUL) of lithium-ion batteries is crucial for enhancing their reliability and safety. Addressing the issue of inaccurate RUL predictions caused by the nonlinear decay resulting from capacity regeneration, this paper proposes an indirect lithium-ion battery RUL pr...