Abstract

This paper proposes a new higher-order sliding mode-based approach to deal with the problem of online state of charge (SOC) and state of health (SOH) estimation for Lithium-ion batteries. The proposed approach is based on the conjunction of a Higher-Order Sliding Mode (HOSM) observer with two Generalized Super-Twisting (GST) observer-based identification algorithms. The HOSM observer provides an exact estimation of SOC, while the two identification algorithms guarantee the finite time estimation of the battery capacity and the battery inner resistance. Thanks to the relationship between the battery capacity and the SOH, an accurate estimation of this latter is obtained. The proposed approach has two main advantages: it ensures SOC estimation using only one observer and estimates the battery parameters without requiring any assumption on the system states. Experimental results using the Worldwide Harmonized Light Vehicles Test procedures (WLTP) are used to illustrate the high efficiency of the proposed approach.

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