The novel state of charge estimation method for lithium battery using sliding mode observer

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

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Critical Review on the Battery State of Charge Estimation Methods for Electric Vehicles

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Combined State of Charge and State of Health estimation over lithium-ion battery cell cycle lifespan for electric vehicles

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Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle (EV) safety and mobility

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Co-Estimation of State of Charge and State of Health for Lithium-Ion Batteries Based on Fractional-Order Calculus

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A review of battery energy storage systems and advanced battery management system for different applications: Challenges and recommendations

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Critical review of on-board capacity estimation techniques for lithium-ion batteries in electric and hybrid electric vehicles

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Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation

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The State of Charge Estimation of Lithium-Ion Batteries Based on a Proportional-Integral Observer

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

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Dynamic electric behavior and open-circuit-voltage modeling of LiFePO4-based lithium ion secondary batteries

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A combined method for state-of-charge estimation for lithium-ion batteries using a long short-term memory network and an adaptive cubature Kalman filter

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Incremental capacity analysis and differential voltage analysis based state of charge and capacity estimation for lithium-ion batteries

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State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles

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Improved Performance of Serially Connected Li-Ion Batteries With Active Cell Balancing in Electric Vehicles

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Co-estimation of state-of-charge, capacity and resistance for lithium-ion batteries based on a high-fidelity electrochemical model

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Estimation of State of Charge, Unknown Nonlinearities, and State of Health of a Lithium-Ion Battery Based on a Comprehensive Unobservable Model

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Electrochemical and Electrostatic Energy Storage and Management Systems for Electric Drive Vehicles: State-of-the-Art Review and Future Trends

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Electro-thermal battery model identification for automotive applications

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On-board state of health estimation of LiFePO4 battery pack through differential voltage analysis

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Co-estimation of capacity and state-of-charge for lithium-ion batteries in electric vehicles

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Kalman filtering techniques for the online model parameters and state of charge estimation of the Li-ion batteries: A comparative analysis

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A modified model based state of charge estimation of power lithium-ion batteries using unscented Kalman filter

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A novel approach for state of charge estimation based on adaptive switching gain sliding mode observer in electric vehicles

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The distribution of relaxation times as basis for generalized time-domain models for Li-ion batteries

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A comparative study of three model-based algorithms for estimating state-of-charge of lithium-ion batteries under a new combined dynamic loading profile

Yang, F., Xing, Y., Wang, D., & Tsui, K. (2015) · Applied Energy · doi:10.1016/j.apenergy.2015.11.072 · Cited by 210

Robust Adaptive Sliding-Mode Observer Using RBF Neural Network for Lithium-Ion Battery State of Charge Estimation in Electric Vehicles

Chen, X., Shen, W., Dai, M., Cao, Z., Jin, J., & Kapoor, A. (2015) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2015.2427659 · Cited by 213

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

A technique for dynamic battery model identification in automotive applications using linear parameter varying structures

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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

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Lithium-ion battery State-of-Charge estimation based on an improved Coulomb-Counting algorithm and uncertainty evaluation

Mohammadi, F. (2022) · Journal of Energy Storage · doi:10.1016/j.est.2022.104061 · Cited by 182

Particle filter-based state-of-charge estimation and remaining-dischargeable-time prediction method for lithium-ion batteries

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Detection of Utilizable Capacity Deterioration in Battery Systems

Roscher, M. A., Aßfalg, J., & Bohlen, O. S. (2010) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2010.2090370 · Cited by 169

State of Charge Estimation for Lithium-Ion Battery Using Recurrent NARX Neural Network Model Based Lighting Search Algorithm

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A Practical Lithium-Ion Battery Model for State of Energy and Voltage Responses Prediction Incorporating Temperature and Ageing Effects

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Model-based real-time thermal fault diagnosis of Lithium-ion batteries

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State of charge estimation of lithium-ion batteries using optimized Levenberg-Marquardt wavelet neural network

Xia, B., Cui, D., Sun, Z. G., Lao, Z., Zhang, R., Wang, W., Sun, W., Lai, Y., & Wang, M. (2018) · Energy · doi:10.1016/j.energy.2018.04.085 · Cited by 157

Combined internal resistance and state-of-charge estimation of lithium-ion battery based on extended state observer

Sun, L. N., Li, G., & You, F. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.109994 · Cited by 151

State of charge estimation of a lithium ion cell based on a temperature dependent and electrolyte enhanced single particle model

Tanim, T. R., Rahn, C. D., & Wang, C. (2015) · Energy · doi:10.1016/j.energy.2014.12.031 · Cited by 143

State of Charge Estimation of Lithium-Ion Batteries Using a Discrete-Time Nonlinear Observer

Li, W., Liang, L., Liu, W., & Wu, X. (2017) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2017.2703685 · Cited by 135

State-of-charge estimation in lithium-ion batteries: A particle filter approach

Tulsyan, A., Tsai, Y., Gopaluni, R. B., & Braatz, R. D. (2016) · Journal of Power Sources · doi:10.1016/j.jpowsour.2016.08.113 · Cited by 133

Critical Review of Intelligent Battery Systems: Challenges, Implementation, and Potential for Electric Vehicles

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A multi-scale parameter adaptive method for state of charge and parameter estimation of lithium-ion batteries using dual Kalman filters

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A Method for Online Capacity Estimation of Lithium Ion Battery Cells Using the State of Charge and the Transferred Charge

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Online Parameter Identification and State of Charge Estimation of Lithium-Ion Batteries Based on Forgetting Factor Recursive Least Squares and Nonlinear Kalman Filter

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Probability based remaining capacity estimation using data-driven and neural network model

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Cell SoC Balancing Using a Cascaded Full-Bridge Multilevel Converter in Battery Energy Storage Systems

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A novel method for state of charge estimation of lithium-ion batteries using a nonlinear observer

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Battery cell state-of-charge estimation using linear parameter varying system techniques

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A comprehensive review of battery state of charge estimation techniques

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Reliable State Estimation of Multicell Lithium-Ion Battery Systems

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Synchronous multi-parameter prediction of battery systems on electric vehicles using long short-term memory networks

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Online estimation of an electric vehicle Lithium-Ion battery using recursive least squares with forgetting

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A Novel Method for Lithium-Ion Battery Online Parameter Identification Based on Variable Forgetting Factor Recursive Least Squares

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Linear parameter varying battery model identification using subspace methods

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Estimating the State-of-Charge of Lithium-Ion Battery Using an H-Infinity Observer Based on Electrochemical Impedance Model

Chen, N., Zhang, P., Dai, J., & Gui, W. (2020) · IEEE Access · doi:10.1109/access.2020.2971002 · Cited by 98

Modeling and Estimation for Advanced Battery Management

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Adaptive parameter identification and State-of-Charge estimation of lithium-ion batteries

Rahimi-Eichi, H., & Chow, M. (2012) · Annual Conference of the IEEE Industrial Electronics Society (IECON) · doi:10.1109/iecon.2012.6389248 · Cited by 94

On-line remaining energy prediction: A case study in embedded battery management system

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Novel methods for estimating lithium-ion battery state of energy and maximum available energy

Zheng, L., Zhu, J., Wang, G., He, T., & Wei, Y. (2016) · Applied Energy · doi:10.1016/j.apenergy.2016.06.031 · Cited by 92

State of charge estimation of an electric vehicle’s battery using Deep Neural Networks: Simulation and experimental results

Fallah, S. E., Kharbach, J., Hammouch, Z., Rezzouk, A., & Jamil, M. O. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.106904 · Cited by 97

Evaluation of Model Based State of Charge Estimation Methods for Lithium-Ion Batteries

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Online SOC and SOH estimation for multicell lithium-ion batteries based on an adaptive hybrid battery model and sliding-mode observer

Kim, T., Qiao, W., & Qu, L. (2013) · IEEE Energy Conversion Congress and Exposition (ECCE) · doi:10.1109/ecce.2013.6646714 · Cited by 90

State of charge estimation for lithium-ion batteries: An adaptive approach

Fang, H., Wang, Y., Şahinoğlu, Z., Wada, T., & Hara, S. (2014) · Control Engineering Practice · doi:10.1016/j.conengprac.2013.12.006 · Cited by 89

State of charge estimation of lithium-ion batteries using an optimal adaptive gain nonlinear observer

Tian, Y., Dong, L., Tian, J., & Xia, B. (2016) · Electrochimica Acta · doi:10.1016/j.electacta.2016.12.119 · Cited by 85

Co-estimation for capacity and state of charge for lithium-ion batteries using improved adaptive extended Kalman filter

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Estimation of Lithium-Ion Batteries State-Condition in Electric Vehicle Applications: Issues and State of the Art

Laadjal, K., & Cardoso, A. J. M. (2021) · Electronics · doi:10.3390/electronics10131588 · Cited by 89

Adaptive gain sliding mode observer for state of charge estimation based on combined battery equivalent circuit model

Chen, X., Shen, W., Cao, Z., & Kapoor, A. (2014) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2014.02.015 · Cited by 85

Dual fuzzy-based adaptive extended Kalman filter for state of charge estimation of liquid metal battery

Cheng, X., Zhang, E., Jiang, K., & Wang, K. (2022) · Applied Energy · doi:10.1016/j.apenergy.2022.120091 · Cited by 81

An online state of charge estimation method with reduced prior battery testing information

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Highly Effective Cell Equalization in a Lithium-Ion Battery Management System

Koseoglou, M., Tsioumas, E., Jabbour, N., & Mademlis, C. (2019) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2019.2920728 · Cited by 80

Adaptive Estimation of the State of Charge for Lithium-Ion Batteries: Nonlinear Geometric Observer Approach

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Dynamical modeling procedure of a Li-ion battery pack suitable for real-time applications

Castano, S., Gauchía, L., Voncilă, E., & Sanz, J. (2015) · Energy Conversion and Management · doi:10.1016/j.enconman.2014.12.076 · Cited by 79

State of Charge Estimation for Power Lithium-Ion Battery Using a Fuzzy Logic Sliding Mode Observer

Zheng, W., Xia, B., Wang, W., Lai, Y., Wang, M., & Wang, H. (2019) · Energies · doi:10.3390/en12132491 · Cited by 78

State estimation of lithium-ion batteries based on strain parameter monitored by fiber Bragg grating sensors

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Current Profile Optimization for Combined State of Charge and State of Health Estimation of Lithium Ion Battery Based on Cramer–Rao Bound Analysis

Song, Z., Wu, X., Li, X., Sun, J., Hofmann, H. F., & Hou, J. Y. (2018) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2018.2877294 · Cited by 75

A Robust State of Charge Estimation Approach Based on Nonlinear Battery Cell Model for Lithium-Ion Batteries in Electric Vehicles

Kim, W., Lee, P., Kim, J., & Kim, K.-S. (2021) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2021.3079934 · Cited by 73

A Novel Intelligent Method for the State of Charge Estimation of Lithium-Ion Batteries Using a Discrete Wavelet Transform-Based Wavelet Neural Network

Cui, D., Xia, B., Zhang, R., Sun, Z., Lao, Z., Wang, W., Sun, W., Lai, Y., & Wang, M. (2018) · Energies · doi:10.3390/en11040995 · Cited by 72

Two Time-Scaled Battery Model Identification With Application to Battery State Estimation

Hu, Y., & Wang, Y.-Y. (2014) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2014.2358846 · Cited by 72

The sequential algorithm for combined state of charge and state of health estimation of lithium-ion battery based on active current injection

Song, Z., Hou, J. Y., Li, X., Wu, X., Hu, X., Hofmann, H. F., & Sun, J. (2019) · Energy · doi:10.1016/j.energy.2019.116732 · Cited by 70

State-of-Charge Estimation Using an EKF-Based Adaptive Observer

Afshar, S., Morris, K., & Khajepour, A. (2018) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2018.2842038 · Cited by 66

Analytic Bound on Accuracy of Battery State and Parameter Estimation

Lin, X., & Stefanopoulou, A. G. (2015) · Journal of The Electrochemical Society · doi:10.1149/2.0791509jes · Cited by 66

On-line scheme for parameter estimation of nonlinear lithium ion battery equivalent circuit models using the simplified refined instrumental variable method for a modified Wiener continuous-time model

Allafi, W., Uddin, K., Zhang, C., Mazuir Raja Ahsan Sha, R., & Marco, J. (2017) · Applied Energy · doi:10.1016/j.apenergy.2017.07.030 · Cited by 66

A Method to Simultaneously Detect the Current Sensor Fault and Estimate the State of Energy for Batteries in Electric Vehicles

Xu, J., Wang, J., Li, S., & Cao, B. (2016) · Sensors · doi:10.3390/s16081328 · Cited by 64

Improved adaptive state-of-charge estimation for batteries using a multi-model approach

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Validation and benchmark methods for battery management system functionalities: State of charge estimation algorithms

Campestrini, C., Horsche, M. F., Zilberman, I., Heil, T., Zimmermann, T., & Jossen, A. (2016) · Journal of Energy Storage · doi:10.1016/j.est.2016.05.007 · Cited by 63

Comparison Study on Two Model-Based Adaptive Algorithms for SOC Estimation of Lithium-Ion Batteries in Electric Vehicles

Tian, Y., Xia, B., Wang, M., Sun, W., & Xu, Z. (2014) · Energies · doi:10.3390/en7128446 · Cited by 62

An Interconnected Observer for Concurrent Estimation of Bulk and Surface Concentration in the Cathode and Anode of a Lithium-ion Battery

Allam, A., & Onori, S. (2018) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2018.2793194 · Cited by 62

State of charge estimation for Lithium Ion cells: Design of experiments, nonlinear identification and fuzzy observer design

Hametner, C., & Jakubek, S. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.04.040 · Cited by 61

Lithium-ion battery state of charge estimation with model parameters adaptation using H ∞ extended Kalman filter

Zhao, L., Liu, Z., & Ji, G. (2018) · Control Engineering Practice · doi:10.1016/j.conengprac.2018.09.010 · Cited by 61

Practical On-Board Measurement of Lithium Ion Battery Impedance Based on Distributed Voltage and Current Sampling

Wei, X., Wang, X., & Dai, H. (2018) · Energies · doi:10.3390/en11010064 · Cited by 60

State of charge estimation of lithium-ion batteries based on an improved parameter identification method

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A State of Charge Estimation Method Based on $H_\infty$ Observer for Switched Systems of Lithium-Ion Nickel–Manganese–Cobalt Batteries

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Characterization and identification towards dynamic-based electrical modeling of lithium-ion batteries

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