A method for state of energy estimation of lithium-ion batteries at dynamic currents and temperatures

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.2004.02.032 · Cited by 1,927 · 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.2004.02.033 · Cited by 1,768 · see citing works

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 · see citing works

State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures

Xing, Y., He, W., Pecht, M., & Tsui, K. L. (2014) · Applied Energy · doi:10.1016/j.apenergy.2013.07.008 · Cited by 977 · 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

2013 IEEE Energy Conversion Congress and Exposition

(2013) · doi:10.1109/ecce20179.2013 · Cited by 386 · see citing works

A new neural network model for the state-of-charge estimation in the battery degradation process

Kang, L., Zhao, X., & Ma, J. (2014) · Applied Energy · doi:10.1016/j.apenergy.2014.01.066 · Cited by 325 · see citing works

Coupled thermal–electrochemical modelling of uneven heat generation in lithium-ion battery packs

Wu, B., Yufit, V., Marinescu, M., Offer, G. J., Martinez-Botas, R., & Brandon, N. P. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.05.164 · Cited by 287 · see citing works

A new model for State-of-Charge (SOC) estimation for high-power Li-ion batteries

He, Y., Liu, X., Zhang, C., & Chen, Z. (2012) · Applied Energy · doi:10.1016/j.apenergy.2012.08.031 · Cited by 276 · see citing works

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 · see citing works

Electro-thermal analysis of Lithium Iron Phosphate battery for electric vehicles

Saw, L. H., Somasundaram, K., Ye, Y., & Tay, A. A. O. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.10.052 · Cited by 244 · see citing works

A novel temperature-compensated model for power Li-ion batteries with dual-particle-filter state of charge estimation

Liu, X., Chen, Z., Zhang, C., & Wu, J. (2014) · Applied Energy · doi:10.1016/j.apenergy.2014.02.072 · Cited by 235 · see citing works

A comparative study on the low-temperature performance of LiFePO4/C and Li3V2(PO4)3/C cathodes for lithium-ion batteries

Rui, X., Jin, Y., Feng, X., Zhang, L., & Chen, C. H. (2010) · Journal of Power Sources · doi:10.1016/j.jpowsour.2010.10.063 · Cited by 234 · see citing works

Kalman filtering state of charge estimation for battery management system based on a stochastic fuzzy neural network battery model

Xu, L., Wang, J., & Chen, Q. (2011) · Energy Conversion and Management · doi:10.1016/j.enconman.2011.06.003 · Cited by 226 · see citing works

Ni3S2 coated ZnO array for high-performance supercapacitors

Xing, Z., Chu, Q., Ren, X., et al. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.07.012 · Cited by 222 · see citing works

Numerical and analytical modeling of lithium ion battery thermal behaviors with different cooling designs

Xun, J., Liu, R., & Jiao, K. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.01.095 · Cited by 217 · see citing works

Adaptive estimation of the electromotive force of the lithium-ion battery after current interruption for an accurate state-of-charge and capacity determination

Waag, W., & Sauer, D. U. (2013) · Applied Energy · doi:10.1016/j.apenergy.2013.05.001 · Cited by 216 · see citing works

LiFePO4 battery pack capacity estimation for electric vehicles based on charging cell voltage curve transformation

Zheng, Y., Lu, L., Han, X., Li, J., & Ouyang, M. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2012.10.057 · Cited by 214 · see citing works

Three-dimensional thermal modeling of a lithium-ion battery pack

Sun, H., Wang, X., Tossan, B., & Dixon, R. (2012) · Journal of Power Sources · doi:10.1016/j.jpowsour.2012.01.081 · Cited by 146 · see citing works

Expanding the Peukert equation for battery capacity modeling through inclusion of a temperature dependency

Hausmann, A., & Depcik, C. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.01.174 · Cited by 145 · see citing works

Modeling the temperature dependence of the discharge behavior of a lithium-ion battery in low environmental temperature

Yi, J., Kim, U., Shin, C., Han, T., & Park, S. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.02.085 · Cited by 122 · see citing works

Adaptive State of Charge Estimation for Li-Ion Batteries Based on an Unscented Kalman Filter with an Enhanced Battery Model

He, Z., Gao, M., Wang, C., Wang, L. Y., & Liu, Y. (2013) · Energies · doi:10.3390/en6084134 · Cited by 112 · see citing works

Definition of a State-of-Energy Indicator (SoE) for Electrochemical Storage Devices: Application for Energetic Availability Forecasting

Mamadou, K., Lemaire, E., Delaille, A., Riu, D., Hing, S. E., & Bultel, Y. (2012) · Journal of The Electrochemical Society · doi:10.1149/2.075208jes · Cited by 73 · see citing works

State of available capacity estimation for lead-acid batteries in electric vehicles using neural network

Shen, W. (2006) · Energy Conversion and Management · doi:10.1016/j.enconman.2006.06.023 · Cited by 70 · see citing works

Robust State of Charge Estimation for Hybrid Electric Vehicles: Framework and Algorithms

Yan, J., Xu, G., Qian, H., & Xu, Y. (2010) · Energies · doi:10.3390/en3101654 · Cited by 51 · see citing works

The state-of-energy: A new criterion for the energetic performances evaluation of electrochemical storage devices

Mamadou, K., Delaille, A., Lemaire-Potteau, E., & Bultel, Y. (2010) · ECS Transactions · doi:10.1149/1.3414008 · Cited by 45 · see citing works

24 th Annual IEEE Applied Power Electronics Conference and Exposition

Wardman, M. (2009) · Cited by 38 · see citing works

Pattern Recognition for Temperature-Dependent State-of-Charge/Capacity Estimation of a Li-ion Cell

Kim, J., & Cho, B. H. (2012) · IEEE Transactions on Energy Conversion · doi:10.1109/tec.2012.2222884 · Cited by 35 · see citing works

Modeling of Lithium Iron Phosphate Batteries by an Equivalent Electrical Circuit: Part II - Model Parameterization as Function of Power and State of Energy (SOE)

Dong, T.-K., Montaru, M., Kirchev, A., Perrin, M., Mattera, F., & Bultel, Y. (2011) · ECS Transactions · doi:10.1149/1.3655706 · Cited by 7 · see citing works

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 · see citing works

A Double-Scale, Particle-Filtering, Energy State Prediction Algorithm for Lithium-Ion Batteries

Xiong, R., Zhang, Y., He, H., Zhou, X., & Pecht, M. G. (2018) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2017.2733475 · Cited by 285 · see citing works

A novel state of health estimation method of Li-ion battery using group method of data handling

Wu, J., Wang, Y., Zhang, X., & Chen, Z. (2016) · Journal of Power Sources · doi:10.1016/j.jpowsour.2016.07.065 · Cited by 235 · see citing works

Review on technological advancement of lithium-ion battery states estimation methods for electric vehicle applications

Shrivastava, P., Naidu, P. A., Sharma, S., Panigrahi, B. K., & Garg, A. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.107159 · Cited by 205 · 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

Adaptive unscented Kalman filter based state of energy and power capability estimation approach for lithium-ion battery

Zhang, W., Shi, W., & Ma, Z. (2015) · Journal of Power Sources · doi:10.1016/j.jpowsour.2015.04.148 · Cited by 178 · see citing works

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

Li, K., Wei, F., Tseng, K. J., & Soong, B.-H. (2018) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2017.2779411 · Cited by 160 · see citing works

Performance prediction and analysis of a PEM fuel cell operating on pure oxygen using data-driven models: A comparison of artificial neural network and support vector machine

Han, I.-S., & Chung, C.-B. (2016) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2016.04.247 · Cited by 141 · see citing works

An online model-based method for state of energy estimation of lithium-ion batteries using dual filters

Dong, G., Chen, Z., Wei, J., Zhang, C., & Wang, P. (2016) · Journal of Power Sources · doi:10.1016/j.jpowsour.2015.10.011 · Cited by 139 · see citing works

A novel Gaussian model based battery state estimation approach: State-of-Energy

He, H., Zhang, Y., Xiong, R., & Wang, C. (2015) · Applied Energy · doi:10.1016/j.apenergy.2015.04.062 · Cited by 127 · see citing works

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 · see citing works

A high-fidelity hybrid lithium-ion battery model for SOE and runtime prediction

Li, K., Soong, B. H., & Tseng, K. J. (2017) · 2017 IEEE Applied Power Electronics Conference and Exposition (APEC) · doi:10.1109/apec.2017.7931032 · Cited by 12 · see citing works

Effect of internal resistance mismatch on performance of battery pack LiFePO4

Perdana, F. A., Supriyanto, A., Purwanto, A., et al. (2016) · International Conference on Electric Vehicular Technology (ICEVT) · doi:10.1109/icimece.2016.7910436 · Cited by 2 · see citing works

Battery parameter identification method of a battery module based on a multi-physical measurement system

Li, X., Chen, F., Lin, S., et al. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.110216 · Cited by 4 · see citing works

Efficient Internal Resistance and Specific Heat Identification of Li-Ion Battery at Low Temperature Conditions

Vega, D. H., Kélouwani, S., & Boulon, L. (2015) · IEEE Vehicle Power and Propulsion Conference (VPPC) · doi:10.1109/vppc.2015.7352939 · Cited by 10 · see citing works

External Transducing Measurement of the Internal Pressure in Sealed Battery by Resistance Strain Gauge

Yang, H., Hu, R., Ai, X., et al. (1998) · Journal of Electrochemistry · doi:10.61558/2993-074x.2705

New Battery Model Integrating the Internal Resistance As a Function of Temperature

Asus, Z., Daud, Z. H. C., Alwi, M. H., et al. (2018) · Journal of Transport System Engineering