DocumentCode
44115
Title
Predictive Control for the Energy Management of a Fuel-Cell–Battery–Supercapacitor Tramway
Author
Torreglosa, Juan P. ; Garcia, Paulo ; Fernandez, Luis M. ; Jurado, Francisco
Author_Institution
Dept. of Electr. Eng., Univ. of Jaen, Jaen, Spain
Volume
10
Issue
1
fYear
2014
fDate
Feb. 2014
Firstpage
276
Lastpage
285
Abstract
This paper evaluates a hybrid powertrain based on fuel cell (FC), battery, and supercapacitor (SC) for the “Urbos 3” tramway, which currently operates powered by SC in the city of Zaragoza, Spain. Due to the dynamic limitations of the main energy source, a proton-exchange-membrane (PEM) FC, other energy secondary sources (ESSs), battery and SC, are needed to supply the vehicle power demand. Moreover, these energy sources allow the energy recovery during regenerative braking. The different sources are connected to a dc bus through dc-dc converters which adapt their variable voltages to the bus voltage and allow the control of energy flow between the sources and the load. The components of the hybrid tramway have been modeled in Matlab/Simulink and are based on commercially available devices. The energy management system used in this work to achieve a proper operation of the energy sources of the hybrid powertrain is based on predictive control. Simulations for the real cycle of the tramway show the suitability of the proposed powertrain and control strategy.
Keywords
DC-DC power convertors; energy management systems; load flow control; power transmission (mechanical); predictive control; proton exchange membrane fuel cells; railway rolling stock; regenerative braking; secondary cells; supercapacitors; ESS; PEM; SC; Spain; Urbos 3 tramway; Zaragoza city; dc bus; dc-dc converter; energy flow control; energy management system; energy recovery; energy secondary source; fuel-cell-battery-supercapacitor tramway; hybrid powertrain; hybrid tramway; predictive control; proton-exchange-membrane FC; regenerative braking; vehicle power demand; Batteries; Discharges (electric); Energy management; Hydrogen; Mathematical model; Predictive control; Vehicles; Batteries; energy management; fuel cells (FCs); predictive control; supercapacitors (SCs); transportation;
fLanguage
English
Journal_Title
Industrial Informatics, IEEE Transactions on
Publisher
ieee
ISSN
1551-3203
Type
jour
DOI
10.1109/TII.2013.2245140
Filename
6450094
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