Read full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=51250#.VGAcpmfHRK0 Author(s) Ala A. Hussein * Affiliation(s) Department of Electrical Engineering, UAE University, Al Ain, UAE . ABSTRACT Battery management systems (BMS) must estimate the state-of-charge (SOC) of the battery accurately to prolong its lifetime and ensure a reliable operation. Since batteries have a wide range of applications, the SOC estimation requirements and methods vary from an application to another. This paper compares two SOC estimation methods, namely extended Kalman filters (EKF) and artificial neural networks (ANN). EKF is a nonlinear optimal estimator that is used to estimate the inner state of a nonl...
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