An Improved Gated Recurrent Unit Network Model for State-of-Charge Estimation of Lithium-Ion Battery

A combined method for state-of-charge estimation for lithium-ion batteries using a long short-term memory network and an adaptive cubature Kalman filter

(2020) Yong Tian et al.   APPLIED ENERGY

A GRU-RNN based momentum optimized algorithm for SOC estimation

(2020) Meng Jiao et al.   JOURNAL OF POWER SOURCES

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

An adaptive working state iterative calculation method of the power battery by using the improved Kalman filtering algorithm and considering the relaxation effect

(2019) Shun-Li Wang et al.   JOURNAL OF POWER SOURCES

Online parameters identification and state of charge estimation for lithium-ion capacitor based on improved Cubature Kalman filter

(2019) Hao Yang et al.   Journal of Energy Storage

Data-efficient parameter identification of electrochemical lithium-ion battery model using deep Bayesian harmony search

(2019) Minho Kim et al.   APPLIED 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

Long Short-Term Memory Networks for Accurate State-of-Charge Estimation of Li-ion Batteries

(2018) Ephrem Chemali et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

A Lithium-Ion Battery-in-the-Loop Approach to Test and Validate Multiscale Dual H Infinity Filters for State-of-Charge and Capacity Estimation

(2018) Cheng Chen et al.   IEEE TRANSACTIONS ON POWER ELECTRONICS

Lithium–Sulfur Battery State-of-Charge Observability Analysis and Estimation

(2018) Abbas Fotouhi et al.   IEEE TRANSACTIONS ON POWER ELECTRONICS

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

A Comparative Study of Three Improved Algorithms Based on Particle Filter Algorithms in SOC Estimation of Lithium Ion Batteries

(2017) Bizhong Xia et al.   Energies

Capacity Prognostics of Lithium-Ion Batteries using EMD Denoising and Multiple Kernel RVM

(2017) Chaolong Zhang et al.   IEEE Access

Adaptive model parameter identification for large capacity Li-ion batteries on separated time scales

(2016) Haifeng Dai et al.   APPLIED ENERGY

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 method for state of energy estimation of lithium-ion batteries based on neural network model

(2015) Guangzhong Dong et al.   ENERGY

Electrochemical Model-Based State of Charge and Capacity Estimation for a Composite Electrode Lithium-Ion Battery

(2015) Alexander Bartlett et al.   IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY

An Adaptive Unscented Kalman Filtering Approach for Online Estimation of Model Parameters and State-of-Charge of Lithium-Ion Batteries for Autonomous Mobile Robots

(2015) Maral Partovibakhsh et al.   IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY

Describing Multimedia Content Using Attention-Based Encoder-Decoder Networks

(2015) Kyunghyun Cho et al.   IEEE TRANSACTIONS ON MULTIMEDIA

A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion olymer battery in electric vehicles

(2013) Rui Xiong et al.   APPLIED ENERGY

Advancements in OCV Measurement and Analysis for Lithium-Ion Batteries

(2013) Mathias Petzl et al.   IEEE TRANSACTIONS ON ENERGY CONVERSION

Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries

(2009) Kong Soon Ng et al.   APPLIED ENERGY