Predictive Algorithm for Optimizing Power Flow in Hybrid Ultracapacitor/Battery Storage Systems for Light Electric Vehicles

This study deals with the optimal control of hybrid energy storage systems for electric vehicle applications. These storage systems can capitalize on the high specific energy of Lithium-Ion batteries and the high specific power of modern ultracapacitors. The new predictive algorithm uses a state-bas...

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Veröffentlicht in:	IEEE transactions on power electronics Jg. 28; H. 8; S. 3882 - 3895
Hauptverfasser:	Laldin, Omar, Moshirvaziri, M., Trescases, O.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.08.2013 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Applied sciences Batteries Battery Battery management Capacitance Capacitors. Resistors. Filters Computer simulation dc-dc converters Dielectric, amorphous and glass solid devices digital control Electric power generation Electric power plants Electric vehicles electric vehicles (EVs) Electrical engineering. Electrical power engineering Electrical power engineering Electronics energy management Energy storage Exact sciences and technology hybrid energy storage Hybrid systems Markov analysis Miscellaneous Operation. Load control. Reliability Optimization algorithms Power networks and lines Power supply Prediction algorithms Real-time systems Regenerative Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices Simulation Storage systems Supercapacitors System-on-a-chip ultracapacitors (u-caps) Various equipment and components Markov process Lithium ion batteries Electric vehicle Energy storage system electric vehicles (EVs) Battery management Optimization Load flow Hybrid system ultracapacitors (u-caps) dc-dc converters Power flow Supercapacitor energy management Trajectory hybrid energy storage Battery storage plants Direct current convertor digital control Storage system Electrolytic capacitor Real time Algorithm Forecasting High power Electrical network High energy Optimal control System simulation Energy demand
ISSN:	0885-8993, 1941-0107
Online-Zugang:	Volltext
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