Determination of state-of-charge and state-of-health of batteries by fuzzy logic methodology

A review on lithium-ion battery ageing mechanisms and estimations for automotive applications

Barré, A., Deguilhem, B., Grolleau, S., Gérard, M., Suard, F., & Riu, D. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.05.040 · Cited by 1,758 · see citing works

Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs

Plett, G. L. (2004) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.02.031 · Cited by 1,385 · see citing works

Critical review of state of health estimation methods of Li-ion batteries for real applications

Berecibar, M., Gandiaga, I., Villarreal, I., Omar, N., Van Mierlo, J., & Van den Bossche, P. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.11.042 · Cited by 1,126 · see citing works

Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles

Waag, W., Fleischer, C., & Sauer, D. U. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.02.064 · Cited by 1,059 · see citing works

A review on prognostics and health monitoring of Li-ion battery

Zhang, J., & Lee, J. (2011) · Journal of Power Sources · doi:10.1016/j.jpowsour.2011.03.101 · Cited by 792 · see citing works

Remaining Useful Life Prediction and State of Health Diagnosis for Lithium-Ion Batteries Using Particle Filter and Support Vector Regression

Wei, J., Dong, G., & Chen, Z. (2018) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2017.2782224 · Cited by 643 · see citing works

Adaptive unscented Kalman filtering for state of charge estimation of a lithium-ion battery for electric vehicles

Sun, F., Hu, X., Zou, Y., & Li, S. (2011) · Energy · doi:10.1016/j.energy.2011.03.059 · Cited by 614 · see citing works

Influence of different open circuit voltage tests on state of charge online estimation for lithium-ion batteries

Zheng, F., Xing, Y., Jiang, J., Sun, B., Kim, J., & Pecht, M. (2016) · Applied Energy · doi:10.1016/j.apenergy.2016.09.010 · Cited by 574 · see citing works

State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network

Yang, F., Li, W., Li, C., & Miao, Q. (2019) · Energy · doi:10.1016/j.energy.2019.03.059 · Cited by 543 · see citing works

Battery management systems in electric and hybrid vehicles

Xing, Y., Ma, E. W. M., Tsui, K. L., & Pecht, M. (2011) · Energies · doi:10.3390/en4111840 · Cited by 540 · see citing works

Prognostics for state of health estimation of lithium-ion batteries based on combination Gaussian process functional regression

Liu, D., Pang, J., Zhou, J., Peng, Y., & Pecht, M. (2013) · Microelectronics Reliability · doi:10.1016/j.microrel.2013.03.010 · Cited by 443 · see citing works

Intelligent prognostics for battery health monitoring based on sample entropy

Widodo, A., Shim, M.-C., Caesarendra, W., & Yang, B.-S. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.03.063 · Cited by 392 · see citing works

Advanced Machine Learning Approach for Lithium-Ion Battery State Estimation in Electric Vehicles

Hu, X., Li, S. E., & Yang, Y. (2016) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2015.2512237 · Cited by 375 · see citing works

Data-driven state of charge estimation of lithium-ion batteries: Algorithms, implementation factors, limitations and future trends

Hossain Lipu, M. S., Hannan, M. A., Hussain, A., Ayob, A., Saad, M. H. M., Karim, T. F., & How, D. N. T. (2020) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2020.124110 · Cited by 378 · see citing works

State-of-Charge Estimation of Lithium-Ion Batteries via Long Short-Term Memory Network

Yang, F., Song, X., Xu, F., & Tsui, K.-L. (2019) · IEEE Access · doi:10.1109/access.2019.2912803 · Cited by 234 · see citing works

A method for state of energy estimation of lithium-ion batteries based on neural network model

Dong, G., Zhang, X., Zhang, C., & Chen, Z. (2015) · Energy · doi:10.1016/j.energy.2015.07.120 · Cited by 187 · see citing works

Improved extended Kalman filter for state of charge estimation of battery pack

Sepasi, S., Ghorbani, R., & Liaw, B. Y. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.12.093 · Cited by 187 · see citing works

Robust prognostics for state of health estimation of lithium-ion batteries based on an improved PSO–SVR model

Qin, T., Zeng, S., & Guo, J. (2015) · Microelectronics Reliability · doi:10.1016/j.microrel.2015.06.133 · Cited by 176 · see citing works

Single-perturbation-cycle online battery impedance spectrum measurement method with closed-loop control of power converter

Qahouq, J. A. A., & Xia, Z. (2017) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2017.2686324 · Cited by 174 · see citing works

Lithium Ion Battery Models and Parameter Identification Techniques

Barcellona, S., & Piegari, L. (2017) · Energies · doi:10.3390/en10122007 · Cited by 149 · see citing works

A new prognostics method for state of health estimation of lithium-ion batteries based on a mixture of Gaussian process models and particle filter

Li, F., & Xu, J. (2015) · Microelectronics Reliability · doi:10.1016/j.microrel.2015.02.025 · Cited by 150 · see citing works

Fuzzy logic modelling of state-of-charge and available capacity of nickel/metal hydride batteries

Singh, P., Fennie, C., & Reisner, D. (2004) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.03.035 · Cited by 117 · see citing works

Fuzzy logic modeling of EIS measurements on lithium-ion batteries

Singh, P., Vinjamuri, R., Wang, X., & Reisner, D. (2006) · Electrochimica Acta · doi:10.1016/j.electacta.2005.02.143 · Cited by 73 · see citing works

Estimation of state of charge for lithium-ion batteries - A Review

A.M.S.M.H.S.Attanayaka, Department of Electrical Engineering, U. O. M., J.P.Karunadasa, & K.T.M.U.Hemapala (2019) · AIMS Energy · doi:10.3934/energy.2019.2.186 · Cited by 72 · see citing works

Review Paper for SOC Estimation Techniques: Challenges and Future Areas for Improvement

Rehman, A. (2024) · Power System Technology · doi:10.52783/pst.906 · Cited by 12 · see citing works

An LSTM-Based Encoder-Decoder Model for State-of-Charge Estimation of Lithium-Ion Batteries

Cui, S., Yong, X., Kim, S., Hong, S., & Joe, I. (2020) · Advances in Intelligent Systems and Computing · doi:10.1007/978-3-030-51965-0_15 · Cited by 8 · see citing works