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Battery State-of-Charge Estimation with Extended Kalman-Filter using Third-Order Thevenin Model

Journal from gdlhub / 2016-11-16 01:30:34
By : Low Wen Yao, Wirun A/l Prayun, Mohd Junaidi Bin Abdul Aziz, Tole Sutikno, Telkomnika
Created : 2015-06-01, with 1 files

Keyword : Lithium Ion Battery, Battery Management System, State of Charge, Extended Kalman Filter, Energy Storage System
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/1467

Lithium-ion battery has become the mainstream energy storage element of the electric vehicle. One of the challenges in electric vehicle development is the state-of-charge estimation of battery. Accurate estimation of state-of-charge is vital to indicate the remaining capacity of the battery and it will eventually maximize the battery performance and ensures the safe operation of the battery. This paper studied on the application of extended Kalman-filter and third order Thevenin equivalent circuit model in state-of-charge estimation of lithium ferro phosphate battery. Random test and pulse discharge test are conducted to obtain the accurate battery model. The simulation and experimental results are compared to validate the proposed state-of-charge estimation method.

Description Alternative :

Lithium-ion battery has become the mainstream energy storage element of the electric vehicle. One of the challenges in electric vehicle development is the state-of-charge estimation of battery. Accurate estimation of state-of-charge is vital to indicate the remaining capacity of the battery and it will eventually maximize the battery performance and ensures the safe operation of the battery. This paper studied on the application of extended Kalman-filter and third order Thevenin equivalent circuit model in state-of-charge estimation of lithium ferro phosphate battery. Random test and pulse discharge test are conducted to obtain the accurate battery model. The simulation and experimental results are compared to validate the proposed state-of-charge estimation method.

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