Journal
INTERNATIONAL JOURNAL OF GREEN ENERGY
Volume 12, Issue 3, Pages 272-278Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/15435075.2014.891512
Keywords
Battery management system; XPC Target; Electric vehicles; Hardware-in-loop; Recursive least square
Funding
- National High Technology Research and Development Program of China [2012AA111603]
- National Key Technology R&D Program of China [2013BAG05B00]
- Program for New Century Excellent Talents in University of China [NCET-11-0785]
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To improve the estimation accuracy of battery's inner state for battery management system, an online parameters identification algorithm for Thevenin battery model is researched. The Thevenin model and parameters identification algorithm based on recursive least square adaptive filter algorithm was built with the Simulink/xPC Target. The results of hardware-in-loop experiment, which uses Federal Urban Driving Schedule test to verify the parameters identification approach, show the proposed approach can accurately identify the model parameters within 1% maximum terminal voltage estimation error, and the State of Charge error which calculated by the open circuit voltage estimates can be efficiently reduced to 4%.
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