State of charge estimation of lithium-ion battery using denoising autoencoder and gated recurrent unit recurrent neural network

Online joint-prediction of multi-forward-step battery SOC using LSTM neural networks and multiple linear regression for real-world electric vehicles

(2020) Jichao Hong et al.   Journal of Energy Storage

State of charge estimation of lithium-ion batteries using hybrid autoencoder and Long Short Term Memory neural networks

(2020) Mohammad Fasahat et al.   JOURNAL OF POWER SOURCES

Robust state of charge estimation based on a sequence-to-sequence mapping model with process information

(2020) Liang Ma et al.   JOURNAL OF POWER SOURCES

State of charge estimation for lithium-ion battery based on an Intelligent Adaptive Extended Kalman Filter with improved noise estimator

(2020) Daoming Sun et al.   ENERGY

Data-driven state of charge estimation of lithium-ion batteries: Algorithms, implementation factors, limitations and future trends

(2020) M.S. Hossain Lipu et al.   JOURNAL OF CLEANER PRODUCTION

An improved adaptive unscented kalman filtering for state of charge online estimation of lithium-ion battery

(2020) Shuzhi Zhang et al.   Journal of Energy Storage

State of charge estimation by multi-innovation unscented Kalman filter for vehicular applications

(2020) Hicham Ben Sassi et al.   Journal of Energy Storage

An Approach to State of Charge Estimation of Lithium-Ion Batteries Based on Recurrent Neural Networks with Gated Recurrent Unit

(2019) Chaoran Li et al.   Energies

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

(2019) Fangfang Yang et al.   ENERGY

Stacked bidirectional long short-term memory networks for state-of-charge estimation of lithium-ion batteries

(2019) Chong Bian et al.   ENERGY

Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries

(2019) Prashant Shrivastava et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

State estimation for advanced battery management: Key challenges and future trends

(2019) Xiaosong Hu et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

State-of-charge sequence estimation of lithium-ion battery based on bidirectional long short-term memory encoder-decoder architecture

(2019) Chong Bian et al.   JOURNAL OF POWER SOURCES

Neural Network Approach for Estimating State of Charge of Lithium-Ion Battery Using Backtracking Search Algorithm

(2018) Mahammad A. Hannan et al.   IEEE Access

State-of-charge estimation of Li-ion batteries using deep neural networks: A machine learning approach

(2018) Ephrem Chemali et al.   JOURNAL OF POWER SOURCES

Research of stacked denoising sparse autoencoder

(2016) Lingheng Meng et al.   NEURAL COMPUTING & APPLICATIONS

Building feature space of extreme learning machine with sparse denoising stacked-autoencoder

(2016) Le-le Cao et al.   NEUROCOMPUTING

Electric vehicle state of charge estimation: Nonlinear correlation and fuzzy support vector machine

(2015) Hanmin Sheng et al.   JOURNAL OF POWER SOURCES