SDTC Neural Network Traction Control of an Electric Vehicle without Differential Gears - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2007

SDTC Neural Network Traction Control of an Electric Vehicle without Differential Gears

Résumé

This paper proposes a Sensorless Direct Torque Control (SDTC) neural network traction control approach of an Electric vehicle (EV) without differential gears (electrical differential system). The EV is in this case propelled by two induction motor (one for each wheel). Indeed, using two electric in-wheel motors give the possibility to have a torque and speed control in each wheel. This control level improves the EV stability and the safety. The proposed traction control system uses the vehicle speed that is different from wheels speed characterized by slip in the driving mode, as an input. In terms of the analysis and the simulations carried out, the conclusion can be drawn that the proposed system is feasible. Simulation results on a test vehicle propelled by two 37-kW induction motors showed that the proposed SDTC neural network approach operates satisfactorily.
Fichier principal
Vignette du fichier
IEEE_VPPC_2007_HADDOUN_1.pdf (969.92 Ko) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-00527618 , version 1 (21-10-2010)

Identifiants

  • HAL Id : hal-00527618 , version 1

Citer

Abdelhakim Haddoun, Farid Khoucha, Mohamed Benbouzid, Demba Diallo, Rachid Abdessemed, et al.. SDTC Neural Network Traction Control of an Electric Vehicle without Differential Gears. IEEE VPPC'07, Sep 2007, Arlington, United States. pp.259-266. ⟨hal-00527618⟩
340 Consultations
210 Téléchargements

Partager

Gmail Mastodon Facebook X LinkedIn More