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References from A closed-loop state of charge estimation of lithium-ion batteries by integrating deep learning and adaptive Kalman filter. Local targets link to admitted publications; unresolved targets remain external evidence.
Synergizing artificial intelligence and battery energy storage systems for a sustainable clean energy transition
10.1016/j.est.2026.120343 · 2026 · External reference
Design and optimization of lithium-ion battery as an efficient energy storage device for electric vehicles: a comprehensive review
10.1016/j.est.2023.108033 · 2023 · External reference
Investigating the error sources of the online state of charge estimation methods for lithium-ion batteries in electric vehicles
10.1016/j.jpowsour.2017.11.094 · 2018 · External reference
Optimal estimation of SoC, SoH using machine learning models and design of a control algorithm for active cell balancing in lithium-ion batteries
2024 · External reference
A review on battery management system and its application in electric vehicle
2021 · External reference
SOC prediction of Li-ion battery based on EKF and CNN-BiLSTM-attention
10.1021/acsomega.5c06451 · 2025 · External reference
A comprehensive review of state of charge estimation in lithium-ion batteries used in electric vehicles
10.1016/j.est.2023.108777 · 2023 · External reference
A critical look at coulomb counting approach for state of charge estimation in batteries
10.3390/en14144074 · 2021 · External reference
Performance analysis of coulomb counting approach for state of charge estimation
2019 · External reference
Open-circuit voltage models for battery management systems: a review
10.3390/en15186803 · 2022 · External reference
Comparative study of the influence of open circuit voltage tests on state of charge online estimation for lithium-ion batteries
10.1109/access.2020.2967563 · 2020 · External reference
An electrochemical impedance model of lithium-ion battery for electric vehicle application
10.1016/j.est.2022.104182 · 2022 · External reference
State of charge prediction of EV Li-ion batteries using EIS: a machine learning approach
10.1016/j.energy.2021.120116 · 2021 · External reference
Evaluation of electrochemical models based battery state-of-charge estimation approaches for electric vehicles
10.1016/j.apenergy.2017.05.109 · 2017 · External reference
Evaluation of various offline and online ECM parameter identification methods of lithium-ion batteries in underwater vehicles
10.1021/acsomega.2c03985 · 2022 · External reference
Unlocking electrochemical model-based online power prediction for lithium-ion batteries via Gaussian process regression
10.1016/j.apenergy.2021.118114 · 2022 · External reference
State-of-charge estimation technique for lithium-ion batteries by means of second-order extended Kalman filter and equivalent circuit model: great temperature robustness state-of-charge estimation
10.1049/pel2.12129 · 2021 · External reference
Co-estimation for capacity and state of charge for lithium-ion batteries using improved adaptive extended Kalman filter
10.1016/j.est.2021.102559 · 2021 · External reference
A modified model based state of charge estimation of power lithium-ion batteries using unscented Kalman filter
10.1016/j.jpowsour.2014.07.143 · 2014 · External reference
Systematic parameter identification of a control-oriented electrochemical battery model and its application for state of charge estimation at various operating conditions
10.1016/j.jpowsour.2020.228153 · 2020 · External reference
A framework for state-of-charge and remaining discharge time prediction using unscented particle filter
10.1016/j.apenergy.2019.114324 · 2020 · External reference
An adaptive fusion estimation algorithm for state of charge of lithium-ion batteries considering wide operating temperature and degradation
10.1016/j.jpowsour.2020.228132 · 2020 · External reference
Improved real-time lithium-ion battery parameter extraction and prediction analysis using ml framework
10.1088/2631-8695/adc657 · 2025 · External reference
Deep learning framework for lithium-ion battery state of charge estimation: recent advances and future perspectives
2023 · External reference
Estimation of SOC for Li-ion battery-powered three-wheeled electric vehicle using machine learning methods
10.1088/2631-8695/ad8063 · 2024 · External reference
A novel temporal-frequency dual attention mechanism network for state of charge estimation of lithium-ion battery
10.1016/j.jpowsour.2024.235374 · 2024 · External reference
State of charge estimation for lithium-ion batteries based on improved barnacle mating optimizer and support vector machine
2022 · External reference
On-line wsn soc estimation using gaussian process regression: an adaptive machine learning approach
10.1016/j.aej.2022.02.067 · 2022 · External reference
Data-driven state of charge estimation for lithium-ion battery packs based on Gaussian process regression
10.1016/j.energy.2020.118000 · 2020 · External reference
SOC estimation of vanadium redox flow batteries based on the ISCSO-ELM algorithm
10.1021/acsomega.3c06113 · 2023 · External reference
State-of-charge estimation of lithium-ion batteries via long short-term memory network
10.1109/access.2019.2912803 · 2019 · External reference
An empirical evaluation of generic convolutional and recurrent networks for sequence modeling
2018 · External reference
A comparative study of different deep learning algorithms for lithium-ion batteries on state-of-charge estimation
10.1016/j.energy.2022.125872 · 2023 · External reference
A novel positional encoded attention-based long short-term memory network for state of charge estimation of lithium-ion battery
10.1016/j.jpowsour.2023.233788 · 2024 · External reference
TTSNet: State-of-charge estimation of Li-ion battery in electrical vehicles with temporal transformer-based sequence network
10.1109/tvt.2024.3350663 · 2024 · External reference
State of charge prediction for lithium-ion batteries based on multi-process scale encoding and adaptive graph convolution
10.1016/j.est.2025.115482 · 2025 · External reference
State-of-charge estimation of lithium-ion battery based on second order resistor-capacitance circuit-PSO-TCN model
10.1016/j.energy.2023.130025 · 2024 · External reference
FECAM: frequency enhanced channel attention mechanism for time series forecasting
10.1016/j.aei.2023.102158 · 2023 · External reference
Evaluating the performances of adaptive Kalman filter methods in GPS/INS integration
10.5081/jgps.9.1.33 · 2010 · External reference
State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures
10.1016/j.apenergy.2013.07.008 · 2014 · External reference
Algorithms for hyper-parameter optimization
2011 · External reference
Squeeze-and-excitation networks
2018 · External reference
FECAM: frequency enhanced channel attention mechanism for time series forecasting
10.1016/j.aei.2023.102158 · ExternalCitation · doi-reference
On-line wsn soc estimation using gaussian process regression: an adaptive machine learning approach
10.1016/j.aej.2022.02.067 · ExternalCitation · doi-reference
State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures
10.1016/j.apenergy.2013.07.008 · ExternalCitation · doi-reference
Evaluation of electrochemical models based battery state-of-charge estimation approaches for electric vehicles
10.1016/j.apenergy.2017.05.109 · ExternalCitation · doi-reference
A framework for state-of-charge and remaining discharge time prediction using unscented particle filter
10.1016/j.apenergy.2019.114324 · ExternalCitation · doi-reference
Unlocking electrochemical model-based online power prediction for lithium-ion batteries via Gaussian process regression
10.1016/j.apenergy.2021.118114 · ExternalCitation · doi-reference
Data-driven state of charge estimation for lithium-ion battery packs based on Gaussian process regression
10.1016/j.energy.2020.118000 · ExternalCitation · doi-reference
State of charge prediction of EV Li-ion batteries using EIS: a machine learning approach
10.1016/j.energy.2021.120116 · ExternalCitation · doi-reference
A comparative study of different deep learning algorithms for lithium-ion batteries on state-of-charge estimation
10.1016/j.energy.2022.125872 · ExternalCitation · doi-reference
State-of-charge estimation of lithium-ion battery based on second order resistor-capacitance circuit-PSO-TCN model
10.1016/j.energy.2023.130025 · ExternalCitation · doi-reference
Co-estimation for capacity and state of charge for lithium-ion batteries using improved adaptive extended Kalman filter
10.1016/j.est.2021.102559 · ExternalCitation · doi-reference
An electrochemical impedance model of lithium-ion battery for electric vehicle application
10.1016/j.est.2022.104182 · ExternalCitation · doi-reference
Design and optimization of lithium-ion battery as an efficient energy storage device for electric vehicles: a comprehensive review
10.1016/j.est.2023.108033 · ExternalCitation · doi-reference
A comprehensive review of state of charge estimation in lithium-ion batteries used in electric vehicles
10.1016/j.est.2023.108777 · ExternalCitation · doi-reference
State of charge prediction for lithium-ion batteries based on multi-process scale encoding and adaptive graph convolution
10.1016/j.est.2025.115482 · ExternalCitation · doi-reference
Synergizing artificial intelligence and battery energy storage systems for a sustainable clean energy transition
10.1016/j.est.2026.120343 · ExternalCitation · doi-reference
A modified model based state of charge estimation of power lithium-ion batteries using unscented Kalman filter
10.1016/j.jpowsour.2014.07.143 · ExternalCitation · doi-reference
Investigating the error sources of the online state of charge estimation methods for lithium-ion batteries in electric vehicles
10.1016/j.jpowsour.2017.11.094 · ExternalCitation · doi-reference
An adaptive fusion estimation algorithm for state of charge of lithium-ion batteries considering wide operating temperature and degradation
10.1016/j.jpowsour.2020.228132 · ExternalCitation · doi-reference
Systematic parameter identification of a control-oriented electrochemical battery model and its application for state of charge estimation at various operating conditions
10.1016/j.jpowsour.2020.228153 · ExternalCitation · doi-reference
A novel positional encoded attention-based long short-term memory network for state of charge estimation of lithium-ion battery
10.1016/j.jpowsour.2023.233788 · ExternalCitation · doi-reference
A novel temporal-frequency dual attention mechanism network for state of charge estimation of lithium-ion battery
10.1016/j.jpowsour.2024.235374 · ExternalCitation · doi-reference
Evaluation of various offline and online ECM parameter identification methods of lithium-ion batteries in underwater vehicles
10.1021/acsomega.2c03985 · ExternalCitation · doi-reference
SOC estimation of vanadium redox flow batteries based on the ISCSO-ELM algorithm
10.1021/acsomega.3c06113 · ExternalCitation · doi-reference
SOC prediction of Li-ion battery based on EKF and CNN-BiLSTM-attention
10.1021/acsomega.5c06451 · ExternalCitation · doi-reference
State-of-charge estimation technique for lithium-ion batteries by means of second-order extended Kalman filter and equivalent circuit model: great temperature robustness state-of-charge estimation
10.1049/pel2.12129 · ExternalCitation · doi-reference
Estimation of SOC for Li-ion battery-powered three-wheeled electric vehicle using machine learning methods
10.1088/2631-8695/ad8063 · ExternalCitation · doi-reference
Improved real-time lithium-ion battery parameter extraction and prediction analysis using ml framework
10.1088/2631-8695/adc657 · ExternalCitation · doi-reference
State-of-charge estimation of lithium-ion batteries via long short-term memory network
10.1109/access.2019.2912803 · ExternalCitation · doi-reference
Comparative study of the influence of open circuit voltage tests on state of charge online estimation for lithium-ion batteries
10.1109/access.2020.2967563 · ExternalCitation · doi-reference
TTSNet: State-of-charge estimation of Li-ion battery in electrical vehicles with temporal transformer-based sequence network
10.1109/tvt.2024.3350663 · ExternalCitation · doi-reference
A critical look at coulomb counting approach for state of charge estimation in batteries
10.3390/en14144074 · ExternalCitation · doi-reference
Open-circuit voltage models for battery management systems: a review
10.3390/en15186803 · ExternalCitation · doi-reference
Evaluating the performances of adaptive Kalman filter methods in GPS/INS integration
10.5081/jgps.9.1.33 · ExternalCitation · doi-reference
