An electric circuit based EV battery model for runtime prediction and state of charge tracking
RIS ID
128933
Abstract
Battery modeling plays a crucial role in improving the performance of battery powered systems especially in electric vehicle (EV) applications. To date, many state-of-the-art battery models have been proposed by researchers to improve the performance of electric vehicles. In this paper, an electric circuit based approach for electric vehicle battery model capable of capturing dynamic capacity rate effects for runtime prediction, state of charge tracking and I-V performance is proposed. To compare the results, two well-known electrical circuit based battery models are accurately modeled in MATLAB Simulink and the accuracy and the simplicity of each model are then compared with the proposed model in this paper with the emphasis on rate capacity effects for state of charge tracking and runtime prediction. To extract the battery parameters and to verify the results of each battery model, experimental tests have also been conducted on four Li-ion LGHG2 3 Ah battery cells connected in series.
Grant Number
ARC/LP130100811
Publication Details
K. Sarrafan, D. Soetanto & K. M. Muttaqi, "An electric circuit based EV battery model for runtime prediction and state of charge tracking," in 2017 IEEE Transportation Electrification Conference (ITEC-India), 2017, pp. 1-6.