A novel Gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve

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Introduction

Li, B., Fernández, C., Yu, C., Liu, D., Stroe, D., Li, H., Liu, K., Xia, L., Peng, Y., Wang, S., et al. (2023) · Elsevier eBooks · doi:10.1016/b978-0-443-16160-5.00007-x

Improved Gated Recurrent Unit Network with Sparrow Search Algorithm for Lithium-Ion Battery State of Health Estimation

Liu, X., Gao, Z., Tian, J., Ma, T., Li, S., Yin, J., & Zhang, Q. (2023) · IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia) · doi:10.1109/icpsasia58343.2023.10294680

Capacity multistage degradation analysis and knee point prediction method of Lithium-ion battery

Wang, T., Zhu, Y., Zhao, W., & Shang, Y. (2023) · CAA International Conference on Vehicular Control and Intelligence (CVCI) · doi:10.1109/cvci59596.2023.10397102

Sorting Strategy for Retired Batteries Based on Voltage Segments

Chen, X., Peng, Q., Meng, J., Wang, J., Gu, T., & Liu, T. (2023) · International Conference on Power Engineering (ICPE) · doi:10.1109/icpe59729.2023.10469405

Machine learning-based aging models for estimating battery state of health and predicting future degradation

Thelen, A. (2023) · doi:10.31274/td-20240329-481

Drone enabled autonomous charging-on-demand

Adegbesan, D. I. (2022) · doi:10.31274/td-20240329-253

Computational and data-enabled approaches for modeling and prognostics of engineered systems

Lui, Y. H. (2021) · doi:10.31274/td-20240329-161

Early disease detection of black gram plant leaf using cloud computing based YOLO V8 model

Motru, V. R., Krishna, S. P., & Sudhir, B. A. (2023) · i-manager s Journal on Information Technology · doi:10.26634/jit.12.4.20209

Elektromobilių baterijų likutinės vertės prognozavimas

Veličkevičius, K. (2024) · Vilnius University Open Series · doi:10.15388/lmitt.2024.19

A Lithium-Ion Batteries Soh Estimation Method Based on Extracting New Features During the Constant Voltage Charging Stage and Improving BpnnPreprint

Xian, Y., Li, M., & Huang, J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4858278

State of Health Estimation for Lithium-Ion Batteries Based on Improved Gaussian Process Regression

Pan, J., Tong, S., Li, Y., Tang, J., Xiong, B., & Chen, Y. (2021) · IEEE ECCE Asia Downunder · doi:10.1109/ecce-asia49820.2021.9479238 · Cited by 3

State of health estimation based on modified Gaussian process regression for lithium-ion batteries

Wang, J., Deng, Z., Yu, T., Yoshida, A., Xu, L., Guan, G., & Abudula, A. (2022) · Journal of Energy Storage · doi:10.1016/j.est.2022.104512 · Cited by 123

SOH estimation for lithium-ion batteries: An improved GPR optimization method based on the developed feature extraction

He, Y. S., Bai, W., Wang, L., Wu, H., & Ding, M. (2024) · Journal of Energy Storage · doi:10.1016/j.est.2024.110678 · Cited by 154

State of health estimation for lithium-ion batteries with Bayesian optimized Gaussian process regression

Ye, L.-H., He, Z., Ke, C.-L., Cheng, X., Zhao, X., Zhang, Z.-X., & Shi, A.-P. (2025) · Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering · doi:10.1177/09544070241287254 · Cited by 2

An Intelligent State of Health Estimation Method for Lithiumion Batteries

Li, H., Peng, R., Zhu, Z., & Zhu, R. (2023) · Advances in transdisciplinary engineering · doi:10.3233/atde230153