DocumentCode :
3418302
Title :
Control strategy optimization for an hybrid parallel powertrain
Author :
Delprat, S. ; Guerra, Thierry Marie ; Paganelli, Gabriele ; Lauber, Jimmy ; Delhom, M.
Author_Institution :
Univ. de Valenciennes et du Hainaut Cambresis
Volume :
2
fYear :
2001
fDate :
2001
Firstpage :
1315
Abstract :
Performances of hybrid vehicles in terms of fuel consumption are strongly related to their control strategy. First studies of this problem deal with instantaneous optimization algorithms (G. Pagnelli, 1999; J. Seiler and D. Schroder, 1998; K. Yamaguchi et al., 1996), designed for real time application. Second studies are based on global optimization algorithms (S. Delprat et al., 1999; S. Rimaux et al., 1999). They outperform instantaneous optimization results, but require a lot of computing time and it seems hard to derive a real time strategy from them. The paper focuses on a control strategy issue applied to the described example of a hybrid parallel single shaft architecture. A global optimization algorithm based on optimal control theory is presented. The results obtained with the optimal theory outperform the ones obtained by local and/or global strategies. A very interesting point is that this method can be easily used for real time application
Keywords :
automobiles; computerised control; electric vehicles; optimal control; real-time systems; automobiles; computing time; control strategy optimization; electric vehicles; fuel consumption; global optimization algorithm; global optimization algorithms; hybrid parallel powertrain; hybrid parallel single shaft architecture; hybrid vehicles; instantaneous optimization algorithms; optimal control theory; real time application; real time strategy; Environmentally friendly manufacturing techniques; Fuels; Internal combustion engines; Mechanical power transmission; Optimal control; Pollution; Prototypes; Shafts; Torque; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2001. Proceedings of the 2001
Conference_Location :
Arlington, VA
ISSN :
0743-1619
Print_ISBN :
0-7803-6495-3
Type :
conf
DOI :
10.1109/ACC.2001.945905
Filename :
945905
Link To Document :
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