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Multi-objective optimization of the sizing of a hybrid electrical vehicle
Author(s) -
Vincent Reinbold,
Laurent Gerbaud,
Emmanuel Vinot
Publication year - 2016
Publication title -
international journal of applied electromagnetics and mechanics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.239
H-Index - 30
eISSN - 1875-8800
pISSN - 1383-5416
DOI - 10.3233/jae-140160
Subject(s) - sizing , driving cycle , automotive engineering , torque , energy management , internal combustion engine , power (physics) , work (physics) , electricity , gasoline , computer science , energy (signal processing) , electric potential energy , process (computing) , engineering , electric vehicle , mechanical engineering , electrical engineering , mathematics , art , statistics , physics , quantum mechanics , visual arts , thermodynamics , waste management , operating system
Hybrid electrical vehicles involve two sources of energy, usually gasoline and electricity. The energy management determines the power sharing between the internal combustion engine and the electrical machine (EM). It is highly dependent on the driving cycle (i.e. the use of the vehicle). In this context, the optimal sizing of the EM is determined by: the driving cycle, the power-train characteristics (i.e. ratios and physical limitations e.g. maximum torque available) and the energy management. The key idea of this work is to involve the driving cycle and the environment of the electrical machine in a global multi-objective optimization process taking into account an optimal energy management and an accurate model of the EM based on magnetic circuit equivalent model

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