G. Paganelli

PSA Peugeot Citroen, Lutetia Parisorum, Île-de-France, France

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Publications (7)2.31 Total impact

  • J.J. Santin · G. Ducard · G. Paganelli
    IEEE Conference on Vehicle Power and Propulsion, Paris, France; 09/2004
  • J. Bernard · Y. Lenoir · S. Delprat · T.M. Guerra · J.J. Santin · G. Paganelli
    Symposium IEEE Vehicle Power and Propulsion 2004Symposium IEEE Vehicle Power and Propulsion 2004; 01/2004
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    G. Paganelli · S. Delprat · T.M. Guerra · J. Rimaux · J.J. Santin
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    ABSTRACT: Hybrid vehicles use at least two energy sources for their propelling. Usually an electric motor is used with an IC engine. Hybrid vehicles are expected to be less polluting and to have a lower fuel consumption than conventional vehicles. This paper presents an algorithm which chooses the power split between the motor and the engine in order to minimize the fuel consumption. First of all, the prototype built at the LAMIH is presented, then the equivalent consumption minimization strategy is described. First results show that a 17.5% of fuel reduction can be achieved for the CEN speed cycle.
    Vehicular Technology Conference, 2002. VTC Spring 2002. IEEE 55th; 02/2002
  • S. Delprat · T.M. Guerra · G. Paganelli · J. Lauber · M. Delhom
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    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
    American Control Conference, 2001. Proceedings of the 2001; 02/2001
  • G. Paganelli · T.M. Guerra · S. Delprat · J.J. Santin · M. Delhom · E. Combes
    Proceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy 01/2000; · 0.65 Impact Factor
  • G. Paganelli · T M Guerra · S. Delprat · J.J. Santin · M. Delhom · E. Combes
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    ABSTRACT: The aim of this paper is to propose a power control strategy for hybrid electrical vehicles. This strategy uses a fuel consumption criterion with battery charge sustaining. It is based on an instantaneous minimization of the equivalent fuel flow. Two comparisons are performed to evaluate the proposed strategy. The first one uses the loss minimization strategy of Seiler and Schröder [1], which appears to be realistic and efficient for real-time control. This strategy is also based on an instantaneous optimization and allows the battery state of charge to be taken into account. The second comparison is made with an optimal solution found for a given driving schedule. Although not realistic for real-time control, this solution is derived through a global optimization algorithm, the well-known simulated annealing method.
    Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering 01/2000; 214(D7-7):705-717. DOI:10.1243/0954407001527583 · 0.83 Impact Factor
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    ABSTRACT: The aim of this paper is to present a study at the University of Valenciennes about an electrical prototype car based on a serial vehicle. The drive system is a natural one with lead batteries and a separately excited direct-current motor; the electronics has been realized with insulated gate bipolar transistors. The current loops, helpful for the electrical engine command, are analogic and are regulated by a fuzzycontroller. The goal of the control was to minimize energy consumption and to optimize performance and confort.
    Cybernetics & Systems 01/1997; 28(8):675-693. · 0.84 Impact Factor