HYBRID MAXIMUMCONTROL STRUCTUREUSING FUZZY LOGICOF ELECTRIC VEHICLE
Résumé
This paper presents a Modelling of traction control system of an Electric Vehicle (EV) based on the Energetic Macroscopic
Representation (EMR) and the Maximum Control Structure (MCS). This last is using Fuzzy Logic Control(FLC) toinvert the
EMR accumulation element for the control task. A developed combination of fuzzy control strategy with SMC combines the
advantages of these two approaches and facilitates the inversion of the accumulation elements. In order to validate the
simulation results, a comparison between the results obtained by MCS using IP controller which has already been developed
by L2EP laboratory (Lille, France) and the presented MSC-FLC obtained by Matlab/Simulink software tool is included
Références
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IEEE 2006. pp.5319--5324
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Tegani and A. Haddi, ”Modeling and Fuzzy logic
Control of Electrical Vehicle with an Adaptive
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Power Engineering, Energy and Electrical Drives,
IEEE-POWERENG13, Istanbul, Turkey, 2013.
[11] Summer school on "Modelling and Control of
electromechanical system using Energetic
Macroscopic Representation Formalism", Labo. L2EP
Lille 2005. France, http://l2ep.univlille1.fr/commande/emr-2009/fr-presentation.htm
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Lemaire-Semail, Y. Le Menach, W. Lhomme and F.
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2007 European ,IEEE. pp. 1-9
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Rashid, "Self learning fuzzy controllers using iterative
learning tuner", International Journal of Digital
Signal Processing, Elsevier. 2010. pp. 289-300.
[14] H. Jabr, D. Lu, and N. Kar, "Design and
Implementation of Neuro-Fuzzy Vector Control for
Wind-driven Doubly-Fed Induction Generator", IEEE
Transactions on Sustainable Energy, IEEE. 2011. pp.
1-1.
[15] T. Nomura and T. Miyoshi, "An adaptive fuzzy rule
extraction using hybrid model of the fuzzy selforganizing map and the genetic algorithm with
numerical chromosomes", Journal of Intelligent and
Fuzzy Systems-Applications in Engineering and
Technology, IOS Press. 1998. pp. 39-52.
"Advancing electricvehicle development with purelead-tin battery technology", Journal of power
sources, Elsevier. 1997 pp. 151-155.
[2] G. S. Caux, W. Hankache, M. Fadel and D. Hissel,
"On-line fuzzy energy management for hybrid fuel
cell systems", International Journal of Hydrogen
Energy, 1010, Elsevier. 1010. pp. 2134-2143.
[3] L. Boulon, M.C. Pera, D. Hissel, A. Bouscayrol and P.
Delarue "Energetic macroscopic representation of a
fuel cell-supercapacitor system", Vehicle Power and
Propulsion Conference, IEEE. 2007, pp. 290-297
[4] A. Bouscayrol, X. Guillaud and P. Delarue,
"Hardware-in-the-loop simulation of a wind energy
conversion system using Energetic Macroscopic
Representation", Industrial Electronics Society, IEEE.
2007. pp. 6-[5] A. Nouh, M. Chami, A. Djerdir and El M. Bagdouri,
"Electric Vehicle Control using the Simulator
ELEVES", Vehicle Power and Propulsion
Conference, IEEE. 2007. pp. 696-701.
[6] W. Lhomme, P. Delarue, P. Barrade and A.
Bouscayrol, "Maximum control structure of a series
hybrid electric vehicle using supercapacitors", Proc.
EVS21, 2005. pp. 8.
[7] O. Kraa, A. Aboubou, A. Henni, M. Becherif, M.Y.
Mohammedi, M.Y. Ayad and M. Bahri, ”Fuzzy Logic
Based Maximum Control Structure of an Electric
Vehicle”, International Conference on Renewable
Energy : Generation and Applications, IEEEICREGA12, United Arab Emirates 2012.
[8] A. Bouscayrol, W. Lhomme, P. Delarue, B. LemaireSemail and S. Aksas, "Hardware-in-the-loop
simulation of electric vehicle traction systems using
Energetic Macroscopic Representation". Conference
on Industrial Electronics, 32nd Annual, IECON,
IEEE 2006. pp.5319--5324
Hybrid maximum control structure using fuzzy logic of electric vehicle
111
[9] W. Lhomme, A. Bouscayrol and P. Barrade,
"Simulation of a series hybrid electric vehicle based
on energetic macroscopic representation"
International Symposium on Industrial Electronics,
,IEEE 2004. pp. 1525-[10] O. Kraa, M. Becherif, A. Aboubou, M.Y. Ayad, I.
Tegani and A. Haddi, ”Modeling and Fuzzy logic
Control of Electrical Vehicle with an Adaptive
Operation Mode”, 4th International Conference on
Power Engineering, Energy and Electrical Drives,
IEEE-POWERENG13, Istanbul, Turkey, 2013.
[11] Summer school on "Modelling and Control of
electromechanical system using Energetic
Macroscopic Representation Formalism", Labo. L2EP
Lille 2005. France, http://l2ep.univlille1.fr/commande/emr-2009/fr-presentation.htm
[12] A. Bouscayrol, A. Bruyère, P. Delarue, F. Girau, B.
Lemaire-Semail, Y. Le Menach, W. Lhomme and F.
Locment,"Teaching drive control using Energetic
Macroscopic Representation-initiation level"
Conference on Power Electronics and Applications,
2007 European ,IEEE. pp. 1-9
[13] S. Ashraf, E. Muhammad, A. Al-Habaibeh and F.
Rashid, "Self learning fuzzy controllers using iterative
learning tuner", International Journal of Digital
Signal Processing, Elsevier. 2010. pp. 289-300.
[14] H. Jabr, D. Lu, and N. Kar, "Design and
Implementation of Neuro-Fuzzy Vector Control for
Wind-driven Doubly-Fed Induction Generator", IEEE
Transactions on Sustainable Energy, IEEE. 2011. pp.
1-1.
[15] T. Nomura and T. Miyoshi, "An adaptive fuzzy rule
extraction using hybrid model of the fuzzy selforganizing map and the genetic algorithm with
numerical chromosomes", Journal of Intelligent and
Fuzzy Systems-Applications in Engineering and
Technology, IOS Press. 1998. pp. 39-52.
Comment citer
KRAA, O. et al.
HYBRID MAXIMUMCONTROL STRUCTUREUSING FUZZY LOGICOF ELECTRIC VEHICLE.
Courrier du Savoir, [S.l.], v. 17, mai 2014.
ISSN 1112-3338.
Disponible à l'adresse : >https://revues.univ-biskra.dz/index.php/cds/article/view/368>. Date de consultation : 26 avr. 2024
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