Modeling and state of charge estimation of Li-ion batteries for vehicular applications
Abstract
Accurate battery models and precise calculation of the battery state of charge (SOC) are necessary for maximizing battery performance, realizing safe operation, and extending the operating range of hybrid electric vehicles. In the technical literature, various battery models have been proposed and investigated. This research, based upon previous work in the field, develops an equivalent circuit model to reflect the battery non-linear dynamic behavior. Taking various temperatures and charging/discharging current rates into consideration, the battery model parameters are extracted based on experimental data. Furthermore, an online SOC estimation method based on the developed model and the Extended Kalman Filter (EKF) is proposed. The accuracy of the battery model and of the SOC estimation method are evaluated and validated based on a set of simulation and experimental studies.
Degree
M.S.E.C.E.
Advisors
SAEEDIFARD, Purdue University.
Subject Area
Electrical engineering
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