Remaining useful life prediction for lithium-ion batteries based on a hybrid model combining the long short-term memory and Elman neural networks

• Published in: Journal of energy storage Vol. 21; pp. 510 - 518
• Main Authors: Li, Xiaoyu, Zhang, Lei, Wang, Zhenpo, Dong, Peng
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.02.2019
• Subjects: Electric vehicles; Elman neural network; Lithium-ion batteries; Long short-term memory; Remaining useful life; Lithium-ion batteries; Long short-term memory; Electric vehicles; Remaining useful life; Elman neural network

This paper presents a novel hybrid Elman-LSTM method for battery remaining useful life prediction by combining the empirical model decomposition algorithm and long short-term memory and Elman neural networks. The empirical model decomposition algorithm is employed to decompose the recorded battery c...