Use of reluctance network modelling and software component to study the influence of electrical machine pole number on hybrid electric vehicle global optimization - Archive ouverte HAL
Article Dans Une Revue Mathematics and Computers in Simulation Année : 2019

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

Résumé

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.
Fichier principal
Vignette du fichier
S0378475418301460.pdf (1.27 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-01826120 , version 1 (21-10-2021)

Licence

Identifiants

Citer

Mathias Le-Guyadec, Laurent Gerbaud, Emmanuel Vinot, Vincent Reinbold, Come Dumont. Use of reluctance network modelling and software component to study the influence of electrical machine pole number on hybrid electric vehicle global optimization. Mathematics and Computers in Simulation, 2019, 34 (1), ⟨10.1016/j.matcom.2018.06.001⟩. ⟨hal-01826120⟩
77 Consultations
58 Téléchargements

Altmetric

Partager

More