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Access Type
WSU Access
Date of Award
January 2011
Degree Type
Thesis
Degree Name
M.S.
Department
Electrical and Computer Engineering
First Advisor
Le Y. Wang
Abstract
Accurate estimation of the state of charge in battery systems is of essential importance for battery system management. Due to nonlinearity, high sensitivity of the inverse mapping from external measurements, and measurement errors, estimation of SOC has remained as a challenging task. This paper introduces an adaptive nonlinear observer design that compensates nonlinearity and achieves better estimation accuracy. A two-time-scale signal processing method is employed to attenuate the effects of measurement noises on SOC estimates. an integrated algorithm is introduced to further identify the internal parameters and initial SOC jointly with a simplified
function of the battery model.
Recommended Citation
Liu, Lezhang, "Integrated system identification and state-of-charge estimation of battery systems" (2011). Wayne State University Theses. 146.
https://digitalcommons.wayne.edu/oa_theses/146