Design an Unscented Kalman Filter-Based SoC Estimator for HEV Application

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An unscented Kalman filter (UKF) is adopted to estimate the state of charge (SoC) of a lithium ion battery for application in hybrid electric vehicles (HEVs). Generally, the extended Kalman filter (EKF) can be selected to estimate a non-linear system state. However, it may leads to large errors since the strong non-linear and stochastic performance. In this paper, the performance of the lithium-ion battery is tested by a design of experiment, such as hysteresis, polarization, coulomb efficiency, etc. And a combined battery model is selected for SoC estimation, while the model parameter was identified by using UKF algorithm. Finally, the federal urban driving schedule (FUDS) is used to evaluate the proposed method accuracy. And the results show that the maximum SoC estimation error is less than 3%.

Info:

Periodical:

Advanced Materials Research (Volumes 588-589)

Edited by:

Lawrence Lim

Pages:

424-428

Citation:

H. W. He et al., "Design an Unscented Kalman Filter-Based SoC Estimator for HEV Application", Advanced Materials Research, Vols. 588-589, pp. 424-428, 2012

Online since:

November 2012

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Price:

$38.00

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