Modeling, Analysis, and Neural Network Control of an EV Electrical Differential

Abstract : This paper presents system modeling, analysis, and simulation of an electric vehicle (EV) with two independent rear wheel drives. The traction control system is designed to guarantee the EV dynamics and stability when there are no differential gears. Using two in-wheel electricmotorsmakes it possible to have torque and speed control in each wheel. This control level improves EV stability and safety. The proposed traction control system uses the vehicle speed, which is different from wheel speed characterized by a slip in the driving mode, as an input. In this case, a generalized neural network algorithm is proposed to estimate the vehicle speed. The analysis and simulations lead to the conclusion that the proposed system is feasible. Simulation results on a test vehicle propelled by two 37-kW induction motors showed that the proposed control approach operates satisfactorily.
Document type :
Journal articles
Complete list of metadatas

Cited literature [29 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00524624
Contributor : Mohamed Benbouzid <>
Submitted on : Friday, October 8, 2010 - 12:56:30 PM
Last modification on : Friday, December 13, 2019 - 10:42:04 AM
Long-term archiving on: Monday, January 10, 2011 - 11:44:59 AM

File

IEEE_TIE_2008_HADDOUN.pdf
Publisher files allowed on an open archive

Identifiers

Citation

Abdelhakim Haddoun, Mohamed Benbouzid, Demba Diallo, Rachid Abdessemed, Jamel Ghouili, et al.. Modeling, Analysis, and Neural Network Control of an EV Electrical Differential. IEEE Transactions on Industrial Electronics, Institute of Electrical and Electronics Engineers, 2008, 55 (6), pp.2286-2294. ⟨10.1109/TIE.2008.918392⟩. ⟨hal-00524624⟩

Share

Metrics

Record views

709

Files downloads

3110