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 :
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