Estimation of State of Charge, Unknown Nonlinearities, and State of Health of a Lithium-Ion Battery Based on a Comprehensive Unobservable Model

Abstract

This paper considers the estimation of the state of charge and state of health for lithium-ion batteries, while an inclusive model is taken into account. The model includes two RC subnetworks, which represent the fast and slow transient responses of the terminal voltage. Nevertheless, the linear part of the model is unobservable. On the other hand, the nonlinear behavior of the open-circuit voltage versus state of charge is also included in the model. The proposed observer tackles the aforementioned problems to attain a reliable estimation of the state of charge. Moreover, as opposed to the methods in which the nonlinearities or uncertainties in the model are disregarded or those terms are discarded using a conventional sliding-mode observer, an analytical method is considered to estimate the additive nonlinear or uncertainty term in the model. This approach leads to a very accurate model of the battery to be used in a battery management system. Moreover, an online parameter estimation method is proposed to estimate the battery's state of health. The proposed scheme benefits from an adaptive rule for the online estimation of the series resistance in the lithium-ion battery based on the accurately identified model. Experimental tests certify the performance and feasibility of the proposed schemes.