Online State of Charge Estimation for Battery of Electric Vehicle Using Sigma-Points Kalman Filters

Online State of Charge Estimation for Battery of Electric Vehicle Using Sigma-Points Kalman Filters

An accurate state-of-charge (SOC) estimation of the hybrid electric vehicle (HEV) and electric vehicle (EV) battery pack is a difficult task to be performed online in a vehicle because of the noisy and low accurate measurements and the wide operating conditions in which the vehicle battery can opera...

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Veröffentlicht in:Applied Mechanics and Materials 2013-09, Vol.427-429 (Mechanical Engineering, Industrial Electronics and Information Technology Applications in Industry), p.824-829
Hauptverfasser: Fang, Li Cun, Xu, Gang, Li, Tian Li, Zhu, Ke Min
Format: Artikel
Sprache:eng
Schlagworte:
Electric batteries
Electric vehicles
Hybrid vehicles
Kalman filters
Lithium batteries
Online
Tasks
Vehicles
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Zusammenfassung:An accurate state-of-charge (SOC) estimation of the hybrid electric vehicle (HEV) and electric vehicle (EV) battery pack is a difficult task to be performed online in a vehicle because of the noisy and low accurate measurements and the wide operating conditions in which the vehicle battery can operate. A Sigma-points Kalman Filters (SPKF) algorithm based on an improved Lithium battery cell model to estimate the SOC of a Lithium battery cell is proposed in this paper. The simulation and experiment results show the effectiveness and ease of implementation of the proposed technique.
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.427-429.824