Reliable state of charge estimation of battery packs using fuzzy adaptive federated filtering

Fuzzy Logic with Engineering Applications

Ross, T. J. (2010) · Wiley eBooks · doi:10.1002/9781119994374 · Cited by 6,659

A comparative study of equivalent circuit models for Li-ion batteries

Hu, X., Li, S., & Peng, H. (2012) · Journal of Power Sources · doi:10.1016/j.jpowsour.2011.10.013 · Cited by 2,179

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.2004.02.033 · Cited by 1,768

Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries

Ng, K. S., Moo, C.-S., Chen, Y.-P., & Hsieh, Y.-C. (2009) · Applied Energy · doi:10.1016/j.apenergy.2008.11.021 · Cited by 1,636

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

State estimation for advanced battery management: Key challenges and future trends

Hu, X., Feng, F., Liu, K., Zhang, L., Xie, J., & Liu, B. (2019) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2019.109334 · Cited by 857

State-of-charge and capacity estimation of lithium-ion battery using a new open-circuit voltage versus state-of-charge

Lee, S., Kim, J., Lee, J.-M., & Cho, B. H. (2008) · Journal of Power Sources · doi:10.1016/j.jpowsour.2008.08.103 · Cited by 699

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

Battery Health Prognosis for Electric Vehicles Using Sample Entropy and Sparse Bayesian Predictive Modeling

Hu, X., Jiang, J., Cao, D., & Egardt, B. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2015.2461523 · Cited by 504

Online cell SOC estimation of Li-ion battery packs using a dual time-scale Kalman filtering for EV applications

Dai, H., Wei, X., Sun, Z., Wang, J., & Gu, W. (2012) · Applied Energy · doi:10.1016/j.apenergy.2012.02.044 · Cited by 367

Internal short circuit detection for battery pack using equivalent parameter and consistency method

Ouyang, M., Zhang, M., Feng, X., Lu, L., Li, J., He, X., & Zheng, Y. (2015) · Journal of Power Sources · doi:10.1016/j.jpowsour.2015.06.087 · Cited by 309

Energy and exergy analyze of PEM fuel cell: A case study of modeling and simulations

Taner, T. (2017) · Energy · doi:10.1016/j.energy.2017.10.102 · Cited by 298

A novel method to obtain the open circuit voltage for the state of charge of lithium ion batteries in electric vehicles by using H infinity filter

Xiong, R., Yu, Q., Wang, L. Y., & Lin, C. (2017) · Applied Energy · doi:10.1016/j.apenergy.2017.05.136 · Cited by 293

Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer

Hu, X., Sun, F., & Zou, Y. (2010) · Energies · doi:10.3390/en3091586 · Cited by 284

Propagation mechanisms and diagnosis of parameter inconsistency within Li-Ion battery packs

Feng, F., Hu, X., Hu, L., Hu, F., Li, Y., & Zhang, L. (2019) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2019.05.042 · Cited by 284

State-of-charge inconsistency estimation of lithium-ion battery pack using mean-difference model and extended Kalman filter

Zheng, Y., Gao, W., Ouyang, M., Lu, L., Zhou, L., & Han, X. (2018) · Journal of Power Sources · doi:10.1016/j.jpowsour.2018.02.058 · Cited by 269

Micro-Short-Circuit Diagnosis for Series-Connected Lithium-Ion Battery Packs Using Mean-Difference Model

Gao, W., Zheng, Y., Ouyang, M., Li, J., Lai, X., & Hu, X. (2018) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2018.2838109 · Cited by 269

Analysis of ageing inhomogeneities in lithium-ion battery systems

Paúl, S., Diegelmann, C., Kabza, H., & Tillmetz, W. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.01.068 · Cited by 251

A method for the estimation of the battery pack state of charge based on in-pack cells uniformity analysis

Zhong, L., Zhang, C., He, Y., & Chen, Z. (2013) · Applied Energy · doi:10.1016/j.apenergy.2013.08.008 · Cited by 247

Experimental investigation of parametric cell-to-cell variation and correlation based on 1100 commercial lithium-ion cells

Rumpf, K., Naumann, M., & Jossen, A. (2017) · Journal of Energy Storage · doi:10.1016/j.est.2017.09.010 · Cited by 223

Cell state-of-charge inconsistency estimation for LiFePO4 battery pack in hybrid electric vehicles using mean-difference model

Zheng, Y., Ouyang, M., Lu, L., Li, J., Han, X., Xu, L., Ma, H., Dollmeyer, T. A., & Freyermuth, V. (2013) · Applied Energy · doi:10.1016/j.apenergy.2013.05.048 · Cited by 212

An improved state of charge estimation method based on cubature Kalman filter for lithium-ion batteries

Peng, J., Luo, J., He, H., & Lü, B. (2019) · Applied Energy · doi:10.1016/j.apenergy.2019.113520 · Cited by 205

A review of equalization strategies for series battery packs: variables, objectives, and algorithms

Feng, F., Hu, X., Liu, J., Lin, X., & Liu, B. (2019) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2019.109464 · Cited by 203

Robustness analysis of State-of-Charge estimation methods for two types of Li-ion batteries

Hu, X., Li, S. E., Peng, H., & Sun, F. (2012) · Journal of Power Sources · doi:10.1016/j.jpowsour.2012.06.005 · Cited by 199

Study on battery pack consistency evolutions and equilibrium diagnosis for serial- connected lithium-ion batteries

Zhang, C., Jiang, Y., Jiang, J., Cheng, G., Diao, W., & Zhang, W. (2017) · Applied Energy · doi:10.1016/j.apenergy.2017.05.176 · Cited by 195

Recognition of battery aging variations for LiFePO4 batteries in 2nd use applications combining incremental capacity analysis and statistical approaches

Jiang, Y., Jiang, J., Zhang, C., Zhang, W., Gao, Y., & Guo, Q. (2017) · Journal of Power Sources · doi:10.1016/j.jpowsour.2017.06.007 · Cited by 194

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

A multi time-scale state-of-charge and state-of-health estimation framework using nonlinear predictive filter for lithium-ion battery pack with passive balance control

Hua, Y., Cordoba-Arenas, A., Warner, N., & Rizzoni, G. (2015) · Journal of Power Sources · doi:10.1016/j.jpowsour.2015.01.112 · Cited by 183

A model-based adaptive state of charge estimator for a lithium-ion battery using an improved adaptive particle filter

Ye, M., Guo, H. N., & Cao, B. (2017) · Applied Energy · doi:10.1016/j.apenergy.2016.12.133 · Cited by 175

An on-line estimation of battery pack parameters and state-of-charge using dual filters based on pack model

Zhang, X., Wang, Y., Yang, D., & Chen, Z. (2016) · Energy · doi:10.1016/j.energy.2016.08.109 · Cited by 143

A novel approach of battery pack state of health estimation using artificial intelligence optimization algorithm

Zhang, X., Wang, Y., Liu, C., & Chen, Z. (2018) · Journal of Power Sources · doi:10.1016/j.jpowsour.2017.11.068 · Cited by 135

Techno‐economic Analysis of a More Efficient Hydrogen Generation System Prototype: A Case Study of PEM Electrolyzer with Cr‐C Coated SS304 Bipolar Plates

Taner, T., Naqvi, S. A. H., & Özkaymak, M. (2019) · Fuel Cells · doi:10.1002/fuce.201700225 · Cited by 131

Joint estimation of lithium-ion battery state of charge and capacity within an adaptive variable multi-timescale framework considering current measurement offset

Jiang, B., Dai, H., Wei, X., & Xu, T. (2019) · Applied Energy · doi:10.1016/j.apenergy.2019.113619 · Cited by 119

Reliable State Estimation of Multicell Lithium-Ion Battery Systems

Roscher, M. A., Bohlen, O. S., & Sauer, D. U. (2011) · IEEE Transactions on Energy Conversion · doi:10.1109/tec.2011.2155657 · Cited by 113

Combined state of charge estimator for electric vehicle battery pack

Wang, J., Cao, B., Chen, Q., & Wang, F. (2007) · Control Engineering Practice · doi:10.1016/j.conengprac.2007.03.004 · Cited by 110

Battery energy storage system modeling: Investigation of intrinsic cell-to-cell variations

Dubarry, M., Pastor-Fernández, C., Baure, G., Yu, T. F., Widanage, W. D., & Marco, J. (2019) · Journal of Energy Storage · doi:10.1016/j.est.2019.02.016 · Cited by 109

A Combined State of Charge Estimation Method for Lithium-Ion Batteries Used in a Wide Ambient Temperature Range

Feng, F., Lu, R., & Zhu, C. (2014) · Energies · doi:10.3390/en7053004 · Cited by 97

On-line battery state-of-charge estimation based on an integrated estimator

Wang, Y., Zhang, C., & Chen, Z. (2015) · Applied Energy · doi:10.1016/j.apenergy.2015.09.015 · Cited by 93

Fuzzy logic and bed-to-wall heat transfer in a large-scale CFBC

Krzywański, J., Wesołowska, M., Błaszczuk, A., Majchrzak, A., Komorowski, M., & Nowak, W. (2017) · International Journal of Numerical Methods for Heat & Fluid Flow · doi:10.1108/hff-09-2017-0357 · Cited by 54

A comparison of fuzzy logic and cluster renewal approaches for heat transfer modeling in a 1296 t/h CFB boiler with low level of flue gas recirculation

Błaszczuk, A., & Krzywański, J. (2017) · Archives of Thermodynamics · doi:10.1515/aoter-2017-0006 · Cited by 52

Multicell state estimation using variation based sequential Monte Carlo filter for automotive battery packs

Li, J., Barillas, J. K., Guenther, C., & Danzer, M. A. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.12.010 · Cited by 46

Real-Time Estimation of Battery State of Charge With Metabolic Grey Model and LabVIEW Platform

Zheng, D. R., Wang, H., An, J., Chen, J., Pan, H., & Chen, L. (2018) · IEEE Access · doi:10.1109/access.2018.2807805 · Cited by 23

A Remaining Discharge Energy Prediction Method for Lithium-Ion Battery Pack Considering SOC and Parameter Inconsistency

Fang, Q., Wei, X., & Dai, H. (2019) · Energies · doi:10.3390/en12060987 · Cited by 15

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

Wang, Z., Feng, G., Zhen, D., Gu, F., & Ball, A. (2021) · Energy Reports · doi:10.1016/j.egyr.2021.08.113 · Cited by 441

General Discharge Voltage Information Enabled Health Evaluation for Lithium-Ion Batteries

Deng, Z., Hu, X., Lin, X., Xu, L., Che, Y., & Hu, L. (2020) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2020.3040010 · Cited by 212

Health Prognosis for Electric Vehicle Battery Packs: A Data-Driven Approach

Hu, X., Che, Y., Lin, X., & Deng, Z. (2020) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2020.2986364 · Cited by 206

Joint estimation of battery state-of-charge and state-of-health based on a simplified pseudo-two-dimensional model

Liu, B., Tang, X., & Gao, F. (2020) · Electrochimica Acta · doi:10.1016/j.electacta.2020.136098 · Cited by 199

State of art on state estimation: Kalman filter driven by machine learning

Bai, Y., Yan, B., Zhou, C., Su, T., & Jin, X. (2023) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2023.100909 · Cited by 190

A curve transformation-based SOC estimation method incorporating cell inconsistency diagnosis for series-connected battery pack

Cui, N., Li, C., Li, C., & Cui, Z. (2025) · Journal of Energy Storage · doi:10.1016/j.est.2025.117747 · Cited by 6

Cell State-of-Charge Estimation for the Multi-cell Series-connected Battery Pack with Model bIas Correction Approach

Xiong, R., & He, H. (2014) · Energy Procedia · doi:10.1016/j.egypro.2014.11.932 · Cited by 7

Adaptive state of charge estimation for battery packs

Sepasi, S. (2014) · ScholarSpace (University of Hawaii at Manoa) · doi:10.13140/rg.2.1.4737.5209 · Cited by 6

State of charge estimation for a parallel battery pack jointly by fuzzy-PI model regulator and adaptive unscented Kalman filter

Peng, S., Miao, Y., Xiong, R., Bai, J., Cheng, M., & Pecht, M. (2024) · Applied Energy · doi:10.1016/j.apenergy.2024.122807 · Cited by 109

Efficient estimation method for State of Charge of multi-cell battery pack considering cell inconsistency

He, Z., Jin, Y., Hu, S., Li, W., & Zhang, X. (2022) · International Journal of Electrochemical Science · doi:10.20964/2022.08.43 · Cited by 7