Author： Kim Daehyun Goh Taedong Park Minjun Kim Sang Woo
Publisher： MDPI
E-ISSN： 1996-1073|8|11|12409-12428
ISSN： 1996-1073
Source： Energies, Vol.8, Iss.11, 2015-11, pp. : 12409-12428
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Abstract
We propose a state-of-charge (SOC) estimation method for Li-ion batteries that combines a fuzzy sliding mode observer (FSMO) with grey prediction. Unlike the existing methods based on a conventional first-order sliding mode observer (SMO) and an adaptive gain SMO, the proposed method eliminates chattering in SOC estimation. In this method, which uses a fuzzy inference system, the gains of the SMO are adjusted according to the predicted future error and present estimation error of the terminal voltage. To forecast the future error value, a one-step-ahead terminal voltage prediction is obtained using a grey predictor. The proposed estimation method is validated through two types of discharge tests (a pulse discharge test and a random discharge test). The SOC estimation results are compared to the results of the conventional first-order SMO-based and the adaptive gain SMO-based methods. The experimental results show that the proposed method not only reduces chattering, but also improves estimation accuracy.
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