Combining empirical mode decomposition and deep recurrent neural networks for predictive maintenance of lithium-ion battery

• Published in: Advanced engineering informatics Vol. 50; p. 101405
• Main Authors: Chen, James C., Chen, Tzu-Li, Liu, Wei-Jun, Cheng, C.C., Li, Meng-Gung
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2021
• Subjects: Bayesian optimization; Deep recurrent neural network; Empirical mode decomposition; Lithium-Ion battery; Predictive maintenance; Remaining useful life; Empirical mode decomposition; Lithium-Ion battery; Deep recurrent neural network; Remaining useful life; Bayesian optimization; Predictive maintenance

Predictive maintenance of lithium-ion batteries has been one of the popular research subjects in recent years. Lithium-ion batteries can be used as the energy supply for industrial equipment, such as automated guided vehicles and battery electric vehicles. Predictive maintenance plays an important r...