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Contribution à l'optimisation globale pour le dimensionnement et la gestion d'énergie de véhicules hybrides électriques basée sur une approche combinatoire

Abstract : Hybridization of power sources for embedded applications becomes an interesting solution to respect environmental legislation and achieve a higher energy efficiency. However, the choice for components sizing and the energy management strategy need to meet specifications while reducing costs. To solve this optimization problems including several types of variables can be complex because of non linearities included in the formulated problem. Therefore the use of effective solving tools, able to provide a reliable solution, is required. In this thesis, a global optimization method is proposed for the design and the optimal control of hybrid vehicles based on combinatorial optimization, particularly on integer linear programming. From a non-linear optimization problem, the initial problem is reformulated into a multitude of integer linear sub-problems for which a parallel Branch & Bound algorithm is executed. In order to solve large-scale problems, a second algorithm based on the Branch & Cut is developed. This method is used for the study of a hybrid power supply system of a mini-excavator electric. The optimization problem, where energy constraints and aging constraints are implemented, is evaluated according to several parameters and specifications. Finally, this approach is also applied for the optimization of trajectories for a synchronized multi-actuators system.
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Submitted on : Monday, September 19, 2016 - 4:08:08 PM
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Alan Chauvin. Contribution à l'optimisation globale pour le dimensionnement et la gestion d'énergie de véhicules hybrides électriques basée sur une approche combinatoire. Génie mécanique [physics.class-ph]. INSA de Lyon, 2015. Français. ⟨NNT : 2015ISAL0101⟩. ⟨tel-01368509⟩

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