DocumentCode
3662484
Title
Robust state-of-charge estimation of ultracapacitors for electric vehicles
Author
Lei Zhang;Steven Su;Xiaosong Hu;David G. Dorrell
Author_Institution
School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China, Faculty of Engineering and Information Technology, University of Technology, Sydney, Sydney, Australia
fYear
2015
fDate
7/1/2015 12:00:00 AM
Firstpage
1296
Lastpage
1301
Abstract
Ultracapacitors (UCs) are an important energy storage technology in automotive and grid applications. They have several advantages, including high power density and extraordinarily long lifespan. Accurate State-of-Charge (SOC) tracking of UCs is critical for the reliability, resilience, and safety in system operation. This paper presents a novel robust H infinity observer in order to realize the SOC estimation of a UC in real time. It is computationally efficient because the observer gain involved in the real-time computation can be readily synthesized offline. In comparison to state-of-the-art Kalman filtering (KF), the developed robust scheme can ensure high estimation accuracy even without prior knowledge of the process and noise measurement statistical properties. More significantly, the H infinity observer proves to be more robust and tolerant to modeling uncertainties arising from the change of operating conditions and/or cell health status. These benefits are experimentally verified.
Keywords
"System-on-chip","Observers","H infinity control","Kalman filters","Robustness","Noise measurement"
Publisher
ieee
Conference_Titel
Industrial Informatics (INDIN), 2015 IEEE 13th International Conference on
ISSN
1935-4576
Electronic_ISBN
2378-363X
Type
conf
DOI
10.1109/INDIN.2015.7281922
Filename
7281922
Link To Document