A review on online state of charge and state of health estimation for lithium-ion batteries in electric vehicles

Energy Reports ◽

10.1016/j.egyr.2021.08.113 ◽

2021 ◽

Vol 7 ◽

pp. 5141-5161

Author(s):

Zuolu Wang ◽

Guojin Feng ◽

Dong Zhen ◽

Fengshou Gu ◽

Andrew Ball

Keyword(s):

Lithium Ion Batteries ◽

Electric Vehicles ◽

Lithium Ion ◽

State Of Charge ◽

State Of Health

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The Co-estimation of State of Charge, State of Health, and State of Function for Lithium-Ion Batteries in Electric Vehicles

IEEE Transactions on Vehicular Technology ◽

10.1109/tvt.2017.2751613 ◽

2018 ◽

Vol 67 (1) ◽

pp. 92-103 ◽

Author(s):

Ping Shen ◽

Minggao Ouyang ◽

Languang Lu ◽

Jianqiu Li ◽

Xuning Feng

Keyword(s):

Lithium Ion Batteries ◽

Charge State ◽

Electric Vehicles ◽

Lithium Ion ◽

State Of Charge ◽

State Of Health

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State of Charge, State of Health and State of Function Co-Estimation of Lithium-Ion Batteries for Electric Vehicles

2016 IEEE Vehicle Power and Propulsion Conference (VPPC) ◽

10.1109/vppc.2016.7791782 ◽

2016 ◽

Author(s):

Ping Shen ◽

Minggao Ouyang ◽

Languang Lu ◽

Jianqiu Li

Keyword(s):

Lithium Ion Batteries ◽

Charge State ◽

Electric Vehicles ◽

Lithium Ion ◽

State Of Charge ◽

State Of Health

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State-of-Charge and State-of-Health Estimation for Lithium-Ion Batteries Based on Dual Fractional-Order Extended Kalman Filter and Online Parameter Identification

IEEE Access ◽

10.1109/access.2021.3068813 ◽

2021 ◽

pp. 1-1

Author(s):

Liuyi Ling ◽

Ying Wei

Keyword(s):

Kalman Filter ◽

Parameter Identification ◽

Lithium Ion Batteries ◽

Extended Kalman Filter ◽

Fractional Order ◽

Lithium Ion ◽

State Of Charge ◽

State Of Health

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A novel bias compensation recursive least square‐multiple weighted dual extended Kalman filtering method for accurate state‐of‐charge and state‐of‐health co‐estimation of lithium‐ion batteries

International Journal of Circuit Theory and Applications ◽

10.1002/cta.3115 ◽

2021 ◽

Author(s):

Jialu Qiao ◽

Shunli Wang ◽

Chunmei Yu ◽

Weihao Shi ◽

Carlos Fernandez

Keyword(s):

Lithium Ion Batteries ◽

Kalman Filtering ◽

Lithium Ion ◽

State Of Charge ◽

Least Square ◽

State Of Health ◽

Recursive Least Square ◽

Extended Kalman Filtering ◽

Filtering Method ◽

Bias Compensation

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A Real-Time Joint Estimator for Model Parameters and State of Charge of Lithium-Ion Batteries in Electric Vehicles

Energies ◽

10.3390/en8088594 ◽

2015 ◽

Vol 8 (8) ◽

pp. 8594-8612 ◽

Author(s):

Jianping Gao ◽

Yongzhi Zhang ◽

Hongwen He

Keyword(s):

Lithium Ion Batteries ◽

Real Time ◽

Electric Vehicles ◽

Lithium Ion ◽

State Of Charge ◽

Model Parameters

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Estimation of State of Charge and State of Health of Lithium‐Ion Batteries Based on a New Adaptive Nonlinear Observer

Advanced Theory and Simulations ◽

10.1002/adts.202100258 ◽

2021 ◽

pp. 2100258

Author(s):

Rajakumar Sakile ◽

Umesh Kumar Sinha

Keyword(s):

Lithium Ion Batteries ◽

Lithium Ion ◽

State Of Charge ◽

Nonlinear Observer ◽

State Of Health

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Monitoring State of Health and State of Charge of Lithium-Ion Batteries Using Machine Learning Techniques

10.1109/catcon52335.2021.9670522 ◽

2021 ◽

Author(s):

Ayush Varshney ◽

Aman Singh ◽

Alka Ann Pradeep ◽

Anu Joseph ◽

Gopakumar P

Keyword(s):

Machine Learning ◽

Lithium Ion Batteries ◽

Lithium Ion ◽

State Of Charge ◽

Machine Learning Techniques ◽

State Of Health ◽

Learning Techniques

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State of Charge and State of Health Estimation of Lithium-Ion Batteries

2018 IEEE 24th International Symposium for Design and Technology in Electronic Packaging (SIITME) ◽

10.1109/siitme.2018.8599196 ◽

2018 ◽

Author(s):

Attila Buchman ◽

Claudiu Lung

Keyword(s):

Lithium Ion Batteries ◽

Lithium Ion ◽

State Of Charge ◽

State Of Health

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Robust Estimation for State-of-Charge and State-of-Health of Lithium-Ion Batteries Using Integral-Type Terminal Sliding-Mode Observers

IEEE Transactions on Industrial Electronics ◽

10.1109/tie.2019.2916389 ◽

2020 ◽

Vol 67 (5) ◽

pp. 4013-4023 ◽

Author(s):

Yong Feng ◽

Chen Xue ◽

Qing-Long Han ◽

Fengling Han ◽

Jiacheng Du

Keyword(s):

Lithium Ion Batteries ◽

Robust Estimation ◽

Sliding Mode ◽

Lithium Ion ◽

State Of Charge ◽

State Of Health ◽

Integral Type ◽

Terminal Sliding Mode ◽

Sliding Mode Observers

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Diagnostics and Prognostics of Lithium-Ion Batteries

Volume 2A: 41st Design Automation Conference ◽

10.1115/detc2015-46935 ◽

2015 ◽

Author(s):

Zhimin Xi ◽

Rong Jing ◽

Cheol Lee

Keyword(s):

Lithium Ion Batteries ◽

Lithium Ion ◽

Remaining Useful Life ◽

State Of Charge ◽

Data Driven ◽

State Of Health ◽

Li Ion Batteries ◽

Battery State Of Charge ◽

Li Ion ◽

This paper investigates recent research on battery diagnostics and prognostics especially for Lithium-ion (Li-ion) batteries. Battery diagnostics focuses on battery models and diagnosis algorithms for battery state of charge (SOC) and state of health (SOH) estimation. Battery prognostics elaborates data-driven prognosis algorithms for predicting the remaining useful life (RUL) of battery SOC and SOH. Readers will learn not only basics but also very recent research developments on battery diagnostics and prognostics.

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