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Fuzzy modelling for the state-of-charge estimation of lead-acid batteries

Abstract:

This paper introduces a novel fuzzy model based structure for the characterisation of discharge processes in lead-acid batteries. This structure is based on a fuzzy model that characterises the relationship between the battery open-circuit voltage (Voc), the state of charge (SoC), and the discharge current. The model is identified and validated using experimental data that is obtained from an experimental system designed to test battery banks with several charge/discharge profiles. For model identification purposes, two standard experimental tests are implemented; one of these tests is used to identify the Voc-SoC curve, while the other helps to identify additional parameters of the model. The estimation of SoC is performed using an Extended Kalman Filter (EKF) with a state transition equation that is based on the proposed fuzzy model. Performance of the proposed estimation framework is compared with other parametric approaches that are inspired on electrical equivalents; e.g., Thevenin, Plett, and Copetti.