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State of Charge Estimation of Lithium-Ion Batteries in Electric Drive Vehicles Using Extended Kalman Filtering

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3 Author(s)
Zheng Chen ; Department of Electrical and Computer Engineering, University of Michigan-Dearborn, Dearborn, MI, USA ; Yuhong Fu ; Chunting Chris Mi

In this paper, a more accurate battery state of charge (SOC) estimation method for electric drive vehicles is developed based on a nonlinear battery model and an extended Kalman filter (EKF) supported by experimental data. A nonlinear battery model is constructed by separating the model into a nonlinear open circuit voltage and a two-order resistance-capacitance model. EKF is used to eliminate the measurement and process noise and remove the need of prior knowledge of initial SOC. A hardware-in-the-loop test bench was built to validate the method. The experimental results show that the proposed method can estimate the battery SOC with high accuracy.

Published in:

IEEE Transactions on Vehicular Technology  (Volume:62 ,  Issue: 3 )