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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
engineering
Modeling, analysis, and neural network control of an EV electrical differential
IEEE Transactions on Industrial Electronics, Volume 55, No. 6, Year 2008
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Description
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 electric motors makes 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. © 2008 IEEE.
Authors & Co-Authors
Haddoun, Abdelhakim
France, Brest
Université de Brest Ubo
Algeria, Oum el Bouaghi
Université Oum el Bouaghi
Benbouzid, Mohamed El Hachemi
France, Brest
Université de Brest Ubo
Diallo, Demba
France, Gif-sur-yvette
Laboratoire de Génie Electrique et Electronique de Paris
Abdessemed, Rachid
Algeria, Batna
Université de Batna 1
Ghouili, Jamel
Canada, Moncton, new Brunswick,
Université de Moncton
Sraïri, Kamel
Algeria, Biskra
Université Mohamed Khider Biskra
Statistics
Citations: 120
Authors: 6
Affiliations: 6
Identifiers
Doi:
10.1109/TIE.2008.918392
ISSN:
02780046