A Study on Battery Management System: Internal Short Circuit Detection and Modeling Methods of Li-ion Batteries Under Various Operating Conditions

Abstract

In this thesis, detection methods for internal short circuit (ISCr) in lithium-ion battery and an innovative model are proposed for the batteries in various operating conditions. Based on equivalent circuit models such as the Rint model and the Thevenin model, the ISCr can be represented by connecting an ISCr resistance parallel to the battery terminals. As fault index, the ISCr resistance, which directly indicates the degree of ISCr faults, is estimated to detect the ISCr early, and the ISCr resistance estimation methods are proposed in different operating environments: (1) battery cells discharged with load profiles for electric vehicles at 25 ℃, (2) battery packs under the identical conditions as in (1), and (3) battery cells charged with constant current at 25 ℃. Additionally, a simple and novel battery modeling method is proposed for batteries that can be used under various ambient temperatures (-10 ℃ to 30 ℃). The proposed methods in this thesis are verified using the experimental data which is obtained with commercial batteries.