DocumentCode :
1361753
Title :
SP-SDP for Fuel Consumption and Tailpipe Emissions Minimization in an EVT Hybrid
Author :
Tate, Ed D. ; Grizzle, J.W. ; Peng, Huei
Author_Institution :
Hybrid Powertrain Eng., Gen. Motors, Troy, MI, USA
Volume :
18
Issue :
3
fYear :
2010
fDate :
5/1/2010 12:00:00 AM
Firstpage :
673
Lastpage :
687
Abstract :
Control strategies have been developed for hybrid electric vehicles (HEV) that minimize fuel consumption while satisfying a charge sustaining constraint. Since one of the components of an HEV is typically the ubiquitous internal combustion engine, tailpipe emissions must also be considered. This paper uses shortest-path stochastic dynamic programming (SP-SDP) to address the minimization of a weighted sum of fuel consumption and tailpipe emissions for an HEV equipped with a dual mode electrically variable transmission (EVT) and a catalytic converter. The shortest path formulation of SDP is chosen to directly address the charge sustaining requirement. Using simple methods, an SP-SDP solution required more than eight thousand hours. Using linear programming and duality, an SP-SDP problem is solved in about three hours on a desktop PC. The resulting time-invariant feedback controller reduces tailpipe emissions by more than 50% when compared to a popular baseline controller.
Keywords :
duality (mathematics); dynamic programming; exhaust systems; feedback; hybrid electric vehicles; internal combustion engines; linear programming; power transmission (mechanical); stochastic programming; EVT hybrid; SP-SDP; catalytic converter; dual mode electrically variable transmission; fuel consumption; hybrid electric vehicles; linear programming; powertrain control; shortest-path stochastic dynamic programming; tailpipe emissions minimization; time-invariant feedback controller; ubiquitous internal combustion engine; Dynamic programming; fuel economy; hybrid electric vehicle; powertrain control;
fLanguage :
English
Journal_Title :
Control Systems Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6536
Type :
jour
DOI :
10.1109/TCST.2009.2023512
Filename :
5229347
Link To Document :
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