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Co-Optimisation du Dimensionnement et du Contrôle des Groupe Motopropulseurs Innovants

Abstract : Advanced technologies are highly demanded in automotive industry to meet the more and more stringent regulations of fuel consumption. Cooptimization of design and control for vehicle propulsion systems with an enhanced computational efficiency is investigated in this thesis.Powertrain components, such as internal combustion engines, batteries, and electric motor/generators, are analytically modeled at descriptive and predictive level correspondingly for the development of fastrunning control optimization and for the scalability of design optimization. The minimal fuel consumption of a hybrid-electric vehicle is evaluated through novel optimization methods. These methods – including the Selective Hamiltonian Minimization, and the GRaphical-Analysis-Based energy Consumption Optimization – are able to evaluate the minimal energy consumption with the enhanced computational efficiency. In addition, the Fully-Analytic energy Consumption Evaluation method approximates the minimal energy consumption in closed form as a function of the mission characteristics and the design parameters of powertrain components.A few case studies are presented in details via the bi-level and uni-level co-optimization approaches, showing an effective improvement in the computational efficiency for the overall co-optimization process.
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https://tel.archives-ouvertes.fr/tel-01694273
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Submitted on : Saturday, January 27, 2018 - 1:01:57 AM
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Jianning Zhao. Co-Optimisation du Dimensionnement et du Contrôle des Groupe Motopropulseurs Innovants. Autre. Université Paris-Saclay, 2017. Français. ⟨NNT : 2017SACLC057⟩. ⟨tel-01694273⟩

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