@inproceedings{8ce6519e26e54d0e8bfad2a09ed67826,
title = "Robust state-of-charge estimation of ultracapacitors for electric vehicles",
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 = "Electric vehicles, Energy storage, Robust observer, State estimation, Ultracapacitor",
author = "Lei Zhang and Steven Su and Xiaosong Hu and Dorrell, \{David G.\}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 13th International Conference on Industrial Informatics, INDIN 2015 ; Conference date: 22-07-2015 Through 24-07-2015",
year = "2015",
month = sep,
day = "28",
doi = "10.1109/INDIN.2015.7281922",
language = "English",
series = "Proceeding - 2015 IEEE International Conference on Industrial Informatics, INDIN 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1296--1301",
booktitle = "Proceeding - 2015 IEEE International Conference on Industrial Informatics, INDIN 2015",
address = "United States",
}