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.
Unscented Kalman Filter based State of Charge Estimation for the Equalization of Lithium-ion Batteries on Electrical Vehicles
2019-12-01
oai:zenodo.org:3566118
Engineering, Technology & Applied Science Research 9(6) 4876-4882
Article (Journal)
Electronic Resource
English
DDC: | 629 |
Unscented Kalman filter for vehicle state estimation
Taylor & Francis Verlag | 2011
|Unscented Kalman filter for vehicle state estimation
Automotive engineering | 2011
|Unscented Kalman filter for vehicle state estimation
Online Contents | 2011
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