DocumentCode :
3762188
Title :
Modeling and control battery aging in energy harvesting systems
Author :
Roberto Valentini;Nga Dang;Marco Levorato;Eli Bozorgzadeh
Author_Institution :
The Donald Bren School of Information and Computer Science, UC Irvine, CA, US
fYear :
2015
Firstpage :
515
Lastpage :
520
Abstract :
Energy storage is a fundamental component for the development of sustainable and environment-aware technologies. One of the critical challenges that needs to be overcome is preserving the State of Health (SoH) in energy harvesting systems, where bursty arrival of energy and load may severely degrade the battery. Tools from Markov process and Dynamic Programming theory are becoming an increasingly popular choice to control dynamics of these systems due to their ability to seamlessly incorporate heterogeneous components and support a wide range of applications. Mapping aging rate measures to fit within the boundaries of these tools is non-trivial. In this paper, a framework for modeling and controlling the aging rate of batteries based on Markov process theory is presented. Numerical results illustrate the tradeoff between battery degradation and task completion delay enabled by the proposed framework.
Keywords :
"Batteries","Aging","Degradation","Smart grids","Measurement","Energy harvesting"
Publisher :
ieee
Conference_Titel :
Smart Grid Communications (SmartGridComm), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/SmartGridComm.2015.7436352
Filename :
7436352
Link To Document :
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