Particle filter for state of charge and state of health estimation for lithium–iron phosphate batteries

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A novel Bayesian multivariate linear regression model for online state-of-health estimation of Lithium-ion battery using multiple health indicators

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State of Health Estimation of Lithium Ion Batteries using Recurrent Neural Network and its Variants

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State of Health Estimation for Lithium-Ion Battery Based on Long Short Term Memory Networks

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Novel method to Estimate SoH of Lithium-Ion Batteries

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A Joint Prediction of the State of Health and Remaining Useful Life of Lithium-Ion Batteries Based on Gaussian Process Regression and Long Short-Term Memory

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State of Health estimation of lithium-ion batteries under multistage constant current fast charging

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Effective capacity early estimation of lithium thionyl chloride batteries for autonomous underwater vehicles

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Real time Diagnostics and Prognostics of UAV Lithium-Polymer Batteries

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Enhancing Lithium-Ion Battery Health Predictions by Hybrid-Grained Graph Modeling

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An analysis and evaluation of state estimation methods for lithium-ion batteries regarding requirements of 48 V HEV applications

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A Generalizable Method for Capacity Estimation and RUL Prediction in Lithium-Ion Batteries

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Recent Trends on Drivetrain Control Strategies and Battery Parameters of a Hybrid Electric Vehicle

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Joint estimation of lithium battery health status and remaining useful life based on convolutional neural networks-long short-term memory networks-locally weighted scatterplot smoothing

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State of Charge Estimation for Li-Ion Batteries: An Edge-Based Data-Driven Approach

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State of charge estimation considering OCV hysteresis in lithium iron phosphate battery for UPS applications

Tjandra, R., Tseng, K. J., Thanagasundram, S., & Jossen, A. (2015) · International Telecommunications Energy Conference (INTELEC) · doi:10.1109/intlec.2015.7572446 · Cited by 4

Development of a Fusion Framework for Lithium-Ion Battery Capacity Estimation in Electric Vehicles

Jiang, B., Wei, X., & Dai, H. (2022) · Batteries · doi:10.3390/batteries8090112 · Cited by 4

A Hybrid State of Charge Estimation Method of a LiFePO4/Graphite Cell Using a Reduced Order Model with an Extended Kalman Filter

Bi, Y., Zhao, X., & Choe, S.-Y. (2019) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.23919/acc.2019.8814310 · Cited by 4

Development of Multifunctional Fiber Optic Sensors for Lithium Ion-Battery Monitoring

Iyer, K. (2016) · UWSpace (University of Waterloo) · Cited by 4

Dynamic Probabilistic Graphical Model applied to the system health diagnosis, prognosis, and the remains useful life estimation

Shahin, K. I. (2020) · doi:10.70675/3a480475zca5fz4645zad44z32eb1d2568e2 · Cited by 4

Integrating Centralized and Decentralized Battery Management Systems using Smart Cell Technology for Enhanced Battery Safety

Faiz, M., Lee, M.-Y., Kang, E., Choi, H., & Jonghoon, K. (2023) · International Conference on Power Electronics and ECCE Asia (ICPE-ECCE Asia) · doi:10.23919/icpe2023-ecceasia54778.2023.10213723 · Cited by 3

Parallel particle filter for state of charge and health estimation with a long term test

Schwunk, S., Straub, S., Armbruster, N., Matting, S., & Vetter, M. (2013) · World Electric Vehicle Symposium and Exhibition (EVS) · doi:10.1109/evs.2013.6914726 · Cited by 5

Estimation of state-of-charge and state-of-health for lithium-ion battery based on improved firefly optimized particle filter

Ouyang, T., Ye, J., Xu, P., Wang, C., & Xu, E. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.107733 · Cited by 24

Novel co‐estimation strategy based on forgetting factor dual particle filter algorithm for the state of charge and state of health of the lithium‐ion battery

Ren, P., Wang, S., Huang, J., Chen, X., He, M., & Cao, W. (2021) · International Journal of Energy Research · doi:10.1002/er.7230 · Cited by 29

Battery state-of-health estimation methods

Wang, S., Fan, Y., Stroe, D., Fernández, C., Yu, C., Cao, W., & Chen, Z. (2021) · Elsevier eBooks · doi:10.1016/b978-0-323-90472-8.00007-x

An Accurate State of Charge Estimation Method for Lithium Iron Phosphate Battery Using a Combination of an Unscented Kalman Filter and a Particle Filter

Nguyen, T.-T., Khan, A. B., Ko, Y., & Choi, W. (2020) · Energies · doi:10.3390/en13174536 · Cited by 21