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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
energy
Online parameter identification of ultracapacitor models using the extended Kalman filter
Energies, Volume 7, No. 5, Year 2014
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Description
Ultracapacitors (UCs) are the focus of increasing attention in electric vehicleand renewable energy system applications due to their excellent performance in terms ofpower density, efficiency, and lifespan. Modeling and parameterization of UCs play animportant role in model-based regulation and management for a reliable and safe operation.In this paper, an equivalent circuit model template composed of a bulk capacitor, asecond-order capacitance-resistance network, and a series resistance, is employed torepresent the dynamics of UCs. The extended Kalman Filter is then used to recursivelyestimate the model parameters in the Dynamic Stress Test (DST) on a specially establishedtest rig. The DST loading profile is able to emulate the practical power sinking andsourcing of UCs in electric vehicles. In order to examine the accuracy of the identifiedmodel, a Hybrid Pulse Power Characterization test is carried out. The validation resultdemonstrates that the recursively calibrated model can precisely delineate the dynamicvoltage behavior of UCs under the discrepant loading condition, and the onlineidentification approach is thus capable of extracting the model parameters in a credible androbust manner. © 2014 by the authors.
Authors & Co-Authors
Zhang, Lei
China, Beijing
Beijing Institute of Technology
Australia, Sydney
University of Technology Sydney
Wang, Zhenpo
China, Beijing
Beijing Institute of Technology
Sun, Fengchun
China, Beijing
Beijing Institute of Technology
Dorrell, David G.
Australia, Sydney
University of Technology Sydney
Statistics
Citations: 87
Authors: 4
Affiliations: 2
Identifiers
Doi:
10.3390/en7053204
ISSN:
19961073