Online state of health prediction method for lithium-ion batteries, based on gated recurrent unit neural networks

State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network

(2019) Fangfang Yang et al.   ENERGY

Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review

(2019) Yi Li et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Long short-term memory recurrent neural network for remaining useful life prediction of lithium-ion batteries

(2018) Yongzhi Zhang et al.   IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY

Remaining useful life estimation of engineered systems using vanilla LSTM neural networks

(2018) Yuting Wu et al.   NEUROCOMPUTING

A review of state of health and remaining useful life estimation methods for lithium-ion battery in electric vehicles: Challenges and recommendations

(2018) M.S. Hossain Lipu et al.   JOURNAL OF CLEANER PRODUCTION

Dynamic Long Short-Term Memory Neural-Network- Based Indirect Remaining-Useful-Life Prognosis for Satellite Lithium-Ion Battery

(2018) Cunsong Wang et al.   Applied Sciences-Basel

LSTM: A Search Space Odyssey

(2017) Klaus Greff et al.   IEEE Transactions on Neural Networks and Learning Systems

Battery state of health estimation: a structured review of models, methods and commercial devices

(2016) Lucian Ungurean et al.   INTERNATIONAL JOURNAL OF ENERGY RESEARCH

Critical review of state of health estimation methods of Li-ion batteries for real applications

(2016) M. Berecibar et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

A survey of mathematics-based equivalent-circuit and electrochemical battery models for hybrid and electric vehicle simulation

(2014) Aden Seaman et al.   JOURNAL OF POWER SOURCES

Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles

(2014) Wladislaw Waag et al.   JOURNAL OF POWER SOURCES

An ensemble model for predicting the remaining useful performance of lithium-ion batteries

(2013) Yinjiao Xing et al.   MICROELECTRONICS RELIABILITY

Prognostics for state of health estimation of lithium-ion batteries based on combination Gaussian process functional regression

(2013) Datong Liu et al.   MICROELECTRONICS RELIABILITY