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Hao Tu, Fanyong Cheng, Miao Li, Yeting Wen
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Synergizing artificial intelligence and battery energy storage systems for a sustainable clean energy transition
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Design and optimization of lithium-ion battery as an efficient energy storage device for electric vehicles: a comprehensive review
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Investigating the error sources of the online state of charge estimation methods for lithium-ion batteries in electric vehicles
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Optimal estimation of SoC, SoH using machine learning models and design of a control algorithm for active cell balancing in lithium-ion batteries
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SOC prediction of Li-ion battery based on EKF and CNN-BiLSTM-attention
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A comprehensive review of state of charge estimation in lithium-ion batteries used in electric vehicles
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A critical look at coulomb counting approach for state of charge estimation in batteries
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Performance analysis of coulomb counting approach for state of charge estimation
datacite
Confidence 0%
2019
Open-circuit voltage models for battery management systems: a review
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Comparative study of the influence of open circuit voltage tests on state of charge online estimation for lithium-ion batteries
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An electrochemical impedance model of lithium-ion battery for electric vehicle application
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State of charge prediction of EV Li-ion batteries using EIS: a machine learning approach
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Evaluation of electrochemical models based battery state-of-charge estimation approaches for electric vehicles
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Evaluation of various offline and online ECM parameter identification methods of lithium-ion batteries in underwater vehicles
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Unlocking electrochemical model-based online power prediction for lithium-ion batteries via Gaussian process regression
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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
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Co-estimation for capacity and state of charge for lithium-ion batteries using improved adaptive extended Kalman filter
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A modified model based state of charge estimation of power lithium-ion batteries using unscented Kalman filter
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Systematic parameter identification of a control-oriented electrochemical battery model and its application for state of charge estimation at various operating conditions
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A framework for state-of-charge and remaining discharge time prediction using unscented particle filter
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An adaptive fusion estimation algorithm for state of charge of lithium-ion batteries considering wide operating temperature and degradation
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Improved real-time lithium-ion battery parameter extraction and prediction analysis using ml framework
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Deep learning framework for lithium-ion battery state of charge estimation: recent advances and future perspectives
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Estimation of SOC for Li-ion battery-powered three-wheeled electric vehicle using machine learning methods
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A novel temporal-frequency dual attention mechanism network for state of charge estimation of lithium-ion battery
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State of charge estimation for lithium-ion batteries based on improved barnacle mating optimizer and support vector machine
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On-line wsn soc estimation using gaussian process regression: an adaptive machine learning approach
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Data-driven state of charge estimation for lithium-ion battery packs based on Gaussian process regression
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SOC estimation of vanadium redox flow batteries based on the ISCSO-ELM algorithm
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State-of-charge estimation of lithium-ion batteries via long short-term memory network
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An empirical evaluation of generic convolutional and recurrent networks for sequence modeling
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A comparative study of different deep learning algorithms for lithium-ion batteries on state-of-charge estimation
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A novel positional encoded attention-based long short-term memory network for state of charge estimation of lithium-ion battery
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TTSNet: State-of-charge estimation of Li-ion battery in electrical vehicles with temporal transformer-based sequence network
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State of charge prediction for lithium-ion batteries based on multi-process scale encoding and adaptive graph convolution
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FECAM: frequency enhanced channel attention mechanism for time series forecasting
10.1016/j.aei.2023.102158 · 2023
Evaluating the performances of adaptive Kalman filter methods in GPS/INS integration
10.5081/jgps.9.1.33 · 2010
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
State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures
10.1016/j.apenergy.2013.07.008 · doi-reference
Evaluating the performances of adaptive Kalman filter methods in GPS/INS integration
10.5081/jgps.9.1.33 · doi-reference
FECAM: frequency enhanced channel attention mechanism for time series forecasting
10.1016/j.aei.2023.102158 · 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 · 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 · 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 · 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 · 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 · doi-reference
State-of-charge estimation of lithium-ion batteries via long short-term memory network
10.1109/access.2019.2912803 · doi-reference
SOC estimation of vanadium redox flow batteries based on the ISCSO-ELM algorithm
10.1021/acsomega.3c06113 · doi-reference
Data-driven state of charge estimation for lithium-ion battery packs based on Gaussian process regression
10.1016/j.energy.2020.118000 · doi-reference
On-line wsn soc estimation using gaussian process regression: an adaptive machine learning approach
10.1016/j.aej.2022.02.067 · 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 · doi-reference
Estimation of SOC for Li-ion battery-powered three-wheeled electric vehicle using machine learning methods
10.1088/2631-8695/ad8063 · doi-reference
Improved real-time lithium-ion battery parameter extraction and prediction analysis using ml framework
10.1088/2631-8695/adc657 · 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 · doi-reference
A framework for state-of-charge and remaining discharge time prediction using unscented particle filter
10.1016/j.apenergy.2019.114324 · 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 · 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 · 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 · 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 · doi-reference
Unlocking electrochemical model-based online power prediction for lithium-ion batteries via Gaussian process regression
10.1016/j.apenergy.2021.118114 · doi-reference
Evaluation of various offline and online ECM parameter identification methods of lithium-ion batteries in underwater vehicles
10.1021/acsomega.2c03985 · doi-reference
Evaluation of electrochemical models based battery state-of-charge estimation approaches for electric vehicles
10.1016/j.apenergy.2017.05.109 · doi-reference
State of charge prediction of EV Li-ion batteries using EIS: a machine learning approach
10.1016/j.energy.2021.120116 · doi-reference
An electrochemical impedance model of lithium-ion battery for electric vehicle application
10.1016/j.est.2022.104182 · 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 · doi-reference
Open-circuit voltage models for battery management systems: a review
10.3390/en15186803 · doi-reference
A critical look at coulomb counting approach for state of charge estimation in batteries
10.3390/en14144074 · doi-reference
A comprehensive review of state of charge estimation in lithium-ion batteries used in electric vehicles
10.1016/j.est.2023.108777 · doi-reference
SOC prediction of Li-ion battery based on EKF and CNN-BiLSTM-attention
10.1021/acsomega.5c06451 · 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 · 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 · doi-reference
Synergizing artificial intelligence and battery energy storage systems for a sustainable clean energy transition
10.1016/j.est.2026.120343 · doi-reference