Date of Award
Summer 8-2014
Degree Type
Thesis
Degree Name
M.S.
Degree Program
Engineering
Department
Electrical Engineering
Major Professor
Huimin Chen
Second Advisor
Rasheed Azzam
Third Advisor
Vesselin Jilkov
Abstract
In battery management systems, the main figure of merit is the battery's SOC, typically obtained from voltage and current measurements. Present estimation methods use simplified battery models that do not fully capture the electrical characteristics of the battery, which are useful for system design. This thesis studied SOC estimation for a lithium-ion battery using a nonlinear, electrical-circuit battery model that better describes the electrical characteristics of the battery. The extended Kalman filter, unscented Kalman filter, third-order and fifth-order cubature Kalman filter, and the statistically linearized filter were tested on their ability to estimate the SOC through numerical simulation. Their performances were compared based on their root-mean-square error over one hundred Monte Carlo runs as well as the time they took to complete those runs. The results show that the extended Kalman filter is a good choice for estimating the SOC of a lithium-ion battery.
Recommended Citation
Zhang, Klaus, "Comparison of Nonlinear Filtering Methods for Battery State of Charge Estimation" (2014). University of New Orleans Theses and Dissertations. 1896.
https://scholarworks.uno.edu/td/1896
Rights
The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.