Remaining useful life prediction of lithium-ion batteries using a hybrid model

Multistep electric vehicle charging station occupancy prediction using hybrid LSTM neural networks

(2022) Tai-Yu Ma et al.   ENERGY

Prognostics of battery cycle life in the early-cycle stage based on hybrid model

(2021) Yu Zhang et al.   ENERGY

Early prediction of battery lifetime via a machine learning based framework

(2021) Zicheng Fei et al.   ENERGY

Useful life prediction based on wavelet packet decomposition and two-dimensional convolutional neural network for lithium-ion batteries

(2021) Pan Ding et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

A method for state-of-charge estimation of lithium-ion batteries based on PSO-LSTM

(2021) Xiaoqing Ren et al.   ENERGY

Remaining useful life and state of health prediction for lithium batteries based on empirical mode decomposition and a long and short memory neural network

(2021) Gong Cheng et al.   ENERGY

A deep learning method for lithium-ion battery remaining useful life prediction based on sparse segment data via cloud computing system

(2021) Qisong Zhang et al.   ENERGY

Stochastic capacity loss and remaining useful life models for lithium-ion batteries in plug-in hybrid electric vehicles

(2020) Andrew Chu et al.   JOURNAL OF POWER SOURCES

A Novel Prognostics Approach Using Shifting Kernel Particle Filter of Li-Ion Batteries Under State Changes

(2020) Seokgoo Kim et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Renewable Energy Sources and Battery Forecasting Effects in Smart Power System Performance

(2019) Mehdi Bagheri et al.   Energies

The accuracy and efficiency of GA and PSO optimization schemes on estimating reaction kinetic parameters of biomass pyrolysis

(2019) Yanming Ding et al.   ENERGY

Ensemble of optimized echo state networks for remaining useful life prediction

(2018) Marco Rigamonti 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

An integrated imputation-prediction scheme for prognostics of battery data with missing observations

(2018) Roozbeh Razavi-Far et al.   EXPERT SYSTEMS WITH APPLICATIONS

RUL Prediction of Deteriorating Products Using an Adaptive Wiener Process Model

(2017) Qingqing Zhai et al.   IEEE Transactions on Industrial Informatics

Length-Changeable Incremental Extreme Learning Machine

(2017) You-Xi Wu et al.   JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY

Gaussian process regression for forecasting battery state of health

(2017) Robert R. Richardson et al.   JOURNAL OF POWER SOURCES

Battery remaining useful life prediction at different discharge rates

(2017) Dong Wang et al.   MICROELECTRONICS RELIABILITY

Fractional order fuzzy control of hybrid power system with renewable generation using chaotic PSO

(2016) Indranil Pan et al.   ISA TRANSACTIONS

A novel health indicator for on-line lithium-ion batteries remaining useful life prediction

(2016) Yapeng Zhou et al.   JOURNAL OF POWER SOURCES

FP-ELM: An online sequential learning algorithm for dealing with concept drift

(2016) Dong Liu et al.   NEUROCOMPUTING

Review of the Remaining Useful Life Prognostics of Vehicle Lithium-Ion Batteries Using Data-Driven Methodologies

(2016) Lifeng Wu et al.   Applied Sciences-Basel

An Integrated Probabilistic Approach to Lithium-Ion Battery Remaining Useful Life Estimation

(2015) Datong Liu et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Advances of aqueous rechargeable lithium-ion battery: A review

(2015) Nurhaswani Alias et al.   JOURNAL OF POWER SOURCES

Application of relevance vector machine and logistic regression for machine degradation assessment

(2009) Wahyu Caesarendra et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING