Modèles mathématiques et techniques d’optimisation non linéaire et combinatoire pour la gestion d’énergie d’un système multi-source : vers une implantation temps-réel pour différentes structures électriques de véhicules hybrides

Abstract : Managing the distribution of electrical energy in a multi-source system (hybrid electric vehicle) is paramount. It increases the system performance by minimizing the fuel used by the primary source, while respecting demand, the differents operating constraints of the energy chain and system security. In this thesis, where the mission profile is known, a combinatorial approach is proposed by modeling the problem of energy management as an optimization pro-blem with constraint satisfaction. The problem is solved using an exact method from operations research, leading to optimal solutions with reduced computation time in comparison with those obtained by applying dynamic programming or optimal control strategies. To test the perturbation sensitivity, robustness study is conducted, based on the analysis of the worst-case solution of the worst scenario, which can be achieved on the vehicle mission profile. In practical cases, the vehicle demand is unknown, and we have only the information about the instantaneous demand, which depends on driving style of the driver. In order to manage on line the energy of the vehicle, an on-line algorithm, based on a fuzzy approach is developed. To measure the quality of the fuzzy solution obtained, a performance study is carried out (finding the optimum solution), using an off-line optimization under reference mission profiles, based on non-linear modeling of the power management problem. The results were used to validate the quality of the resulting fuzzy solution.
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Yacine Gaoua. Modèles mathématiques et techniques d’optimisation non linéaire et combinatoire pour la gestion d’énergie d’un système multi-source : vers une implantation temps-réel pour différentes structures électriques de véhicules hybrides. Energie électrique. Institut National Polytechnique de Toulouse (INP Toulouse), 2014. Français. ⟨tel-01096744⟩

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