@inproceedings{350c3d3f184a47188955ad0f0718fa47,
title = "A novel adaptive sliding mode observer for SOC estimation of lithium batteries in electric vehicles",
abstract = "On the basis of the established second order RC equivalent circuit model, a novel adaptive sliding mode observer (ASMO) is proposed to estimate the state of charge (SOC) of lithium battery in the electric vehicle. The ASMO can adaptively adjust the switching gain according to the system output deviation. The Lyapunov stability theory is employed to prove the convergence of ASMO. Three different discharge curves are carried out, and the comparisons with conventional sliding mode observer (CSMO) and adaptive extended Kalman filter (AEKF) are also presented to evaluate the performance of ASMO. The results show that: (1) compared with CSMO, ASMO can solve the contradiction between the SOC convergence speed and the chattering (2) compared with AEKF, ASMO has the similar SOC estimation accuracy, but possesses faster convergence speed, stronger robustness and less computation time.",
keywords = "Equivalent circuit model, lithium battery, sliding mode observer, SOC estimation",
author = "Huangfu, {Y. G.} and Xu, {J. N.} and Zhuo, {S. R.} and Xie, {M. C.} and Liu, {Y. T.}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer and Security, PESA 2017 ; Conference date: 12-12-2017 Through 14-12-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/PESA.2017.8277750",
language = "英语",
series = "2017 7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer and Security, PESA 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--6",
editor = "Cheng, {K.W. Eric}",
booktitle = "2017 7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer and Security, PESA 2017",
}