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Use of reluctance network modelling and software component to study the influence of electrical machine pole number on hybrid electric vehicle global optimization

By Mathias LE-GUYADEC, Laurent Gerbaud, Emmanuel Vinot, Vincent Reinbold and Come DUMONT

Abstract

In the paper, the global optimization of hybrid electric vehicle (HEV) components and control is performed using genetic algorithm and dynamic programming. Reluctance network modelling (RNM) is used to describe the behaviour of the electrical machine (EM). The pole number is considered as a design variable in the EM model. A software component is built from this model and is used in Matlab for a sizing by optimization. The influence of the EM pole number on the system optimization is analysed. Contrary to the low differences observed on the energy efficiency of the vehicle, the machine shape is highly impacted

Topics: HYBRID ELECTRIC VEHICLE, GLOBAL OPTIMIZATION, INTERIOR PERMANENT MAGNET SYNCHRONOUS MACHINE, POLE NUMBER, RELUCTANCE NETWORK MODEL, MACHINE SYNCHRONE, VEHICULE ELECTRIQUE, VEHICULE HYBRIDE, OPTIMISATION, [SPI]Engineering Sciences [physics]
Publisher: 'Elsevier BV'
Year: 2018
DOI identifier: 10.1016/j.matcom.2018.06.001
OAI identifier: oai:HAL:hal-01826120v1
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