• 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