Electrical Circuit-Based Modeling of a Non-Aqueous Lithium-Oxygen Battery for High Accuracy State-of-Charge Estimation

With the increased interest in electric-powered transportation such as electric vehicle (EV) and hybrid electric vehicle (HEV) application, lithium-ion cell and large-format lithium-polymer cell were taken it for granted that they have become more preferable selection. Unfortunately, they are still limited to the application that requires much higher specific energy density. As a result, in order to overcome an aforementioned problem, non-aqueous lithium-oxygen (Li-O₂) batteries have attracted substantial attention because of their high energy density. Moreover, the need for accurate and reliable state-of-charge (SOC) information which is considered as one of the key factors in battery management system (BMS) is significantly increased for supporting optimal battery performance and safety. So far, no definitive solution has been provided to this question. Therefore, this research gives insight to the design and implementation of the electrical circuit-based modeling of a non-aqueous lithium-oxygen battery for high accuracy SOC estimation. Four experimental tests including discharge capacity/impedance tests with cycling, open-circuit voltage (OCV) test and discharging/charging cycling test were priorly implemented for a detailed analysis of electrochemical characteristic analysis and parameters identification of a non-aqueous lithium-oxygen battery. Through these tasks, it can be completely succeeded in constructing a finalized electrical circuit-based model that consists of the OCV, one series resistance and one RC-ladder with dynamic characteristic. This model enables us to provide appropriate information for high accuracy and reliable SOC estimation based on the extended Kalman filter (EKF). This research has been extensively validated by additional experimental results conducted on a non-aqueous lithium-oxygen battery that had a rated capacity of 1700mAh/g by the ‘Materials and Electro-Chemistry Laboratory in Inha University’. Consequently, it can be well known that all verification results clearly indicate the robustness of the proposed research.