Online parameters identification and state of charge estimation for lithium‐ion batteries using improved adaptive dual unscented Kalman filter

2020 ◽  
Vol 45 (1) ◽  
pp. 975-990 ◽  
Author(s):  
Nian Peng ◽  
Shuzhi Zhang ◽  
Xu Guo ◽  
Xiongwen Zhang
Keyword(s):  
Kalman Filter ◽  
Lithium Ion Batteries ◽  
Unscented Kalman Filter ◽  
Lithium Ion ◽  
State Of Charge ◽  
Parameters Identification ◽  
State Of Charge Estimation

scholarly journals A New State of Charge Estimation Algorithm for Lithium-Ion Batteries Based on the Fractional Unscented Kalman Filter

Energies ◽  
2017 ◽  
Vol 10 (9) ◽  
pp. 1313 ◽  
Author(s):  
Yixing Chen ◽  
Deqing Huang ◽  
Qiao Zhu ◽  
Weiqun Liu ◽  
Congzhi Liu ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Lithium Ion Batteries ◽  
Unscented Kalman Filter ◽  
Lithium Ion ◽  
Estimation Algorithm ◽  
State Of Charge ◽  
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.

scholarly journals State of charge estimation for lithium-ion batteries based on adaptive dual Kalman filter

2020 ◽  
Vol 77 ◽  
pp. 1255-1272 ◽  
Author(s):  
Yidan Xu ◽  
Minghui Hu ◽  
Anjian Zhou ◽  
Yunxiao Li ◽  
Shuxian Li ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
State Of Charge ◽  
State Of Charge Estimation
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