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

Energies ◽  
2013 ◽  
Vol 6 (8) ◽  
pp. 4134-4151 ◽  
Author(s):  
Zhiwei He ◽  
Mingyu Gao ◽  
Caisheng Wang ◽  
Leyi Wang ◽  
Yuanyuan Liu
Keyword(s):  
Kalman Filter ◽  
Unscented Kalman Filter ◽  
State Of Charge ◽  
Li Ion Batteries ◽  
Battery Model ◽  
Li Ion ◽  
State Of Charge Estimation

scholarly journals Improved state of charge estimation for Li-ion batteries using fractional order extended Kalman filter

2019 ◽  
Vol 435 ◽  
pp. 226710 ◽  
Author(s):  
Kodjo S.R. Mawonou ◽  
Akram Eddahech ◽  
Didier Dumur ◽  
Dominique Beauvois ◽  
Emmanuel Godoy
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Fractional Order ◽  
State Of Charge ◽  
Li Ion Batteries ◽  
Li Ion ◽  
State Of Charge Estimation

scholarly journals Unscented Kalman Filter based State of Charge Estimation for the Equalization of Lithium-ion Batteries on Electrical Vehicles

2019 ◽  
Vol 9 (6) ◽  
pp. 4876-4882
Author(s):  
Y. Muratoglu ◽  
A. Alkaya
Keyword(s):  
Kalman Filter ◽  
Lithium Ion Batteries ◽  
Lithium Ion Battery ◽  
Unscented Kalman Filter ◽  
Balance Control ◽  
Lithium Ion ◽  
State Of Charge ◽  
Model Parameters ◽  
Battery Model ◽  
State Of Charge Estimation

Accurate state of charge estimation and robust cell equalization are vital in optimizing the battery management system and improving energy management in electric vehicles. In this paper, the passive balance control based equalization scheme is proposed using a combined dynamic battery model and the unscented Kalman filter based state of charge estimation. The lithium-ion battery is modeled with a 2nd order Thevenin equivalent circuit. The combined dynamic model of the lithium-ion battery, where the model parameters are estimated depending on the state of charge, and the unscented Kalman filter based state of charge, are used to improve the performance of the passive balance control based equalization. The experimental results verified the superiority of the combined dynamic battery model and the unscented Kalman filter algorithm with very tight error bounds. Furthermore, these results showed that the presented passive balance control based equalization scheme is suitable for the equalization of series-connected lithium-ion batteries.

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