Mots Clés de Recherche :
Electronics,Microcontroller, Microprocessor,DSP, FPGA, Dspace.
Electrical engineering, Renewable energy, Control systems, Power electronics, Electric vehicles,Electric drive.
BOUGUENNA IBRAHIM FAROUK received his Engineer degree
and Master in Electronics from University of Science and Technology
Oran Algeria. Also, he received Ph.D. in Electronics ,option control & systems from the University of Sidi Bel Abbes Algeria. his research includes Theory Control, Artificial intelligence,Self driving car, Electric vehicle , Electric drive system, power energy conversion, green transportation.
Axes et thèmes de recherche
Control systems
Power electronics
Model Predictive Control applied on electric drive systems
La revue : International Journal of Power Electronics and Drive System (IJPEDS)
Domaine : Electrical Engineering
Mots Clés : Dynamics Electric vehicle Fuzzy sliding PMSM Sliding mode control
Auteur : I. F.Bouguenna, A.Azaiz, A. Tahour
Issn : 2088-8694 Eissn : vol : 8, Num : 3, pp : 1050-1061
Date de publication : 2017-09-01
Résume : This paper present a speed hybrid fuzzy-sliding mode control (HFSMC) of a
permanent magnet synchronous motor (PMSM) to ensure the traction of an
electric vehicle; at the first we applied the sliding mode control (SMC) with
three surfaces on the PMSM by taking into account the dynamics of the
vehicle; And afterwards we applied the fuzzy-sliding mode in which the
surface of the speed is replaced by a Fuzzy-PI controller; Simulation under
Matlab/Simulink has been carried out to evaluate the efficiency
and robustness of the proposed control on a system drive. It should be noted
that the reference speed is the European urban driving schedule ECE-15
cycle.
La revue : E3S Web Conf.
Domaine : Electrical Engineering
Mots Clés : Electric vehicleDynamicPMSMNeuro-fuzzy sliding mode controlExtended state observer ESO
Auteur : I. F.Bouguenna, A.Azaiz, A. Tahour
Issn : Eissn : 2267-1242 vol : 61, Num : 7, pp :
Date de publication : 2018-10-31
Résume : In this paper a neuro-fuzzy-sliding mode control (NFSMC) with extended state observer (ESO) technique; is designed to guarantee the traction of an electric vehicle with two distinct permanent magnet synchronous motor (PMSM). Each PMSM systems (source-convertermotor) are attached to an electronic differential (ED), in order to adjust the senses of direction of the vehicle, and sustain a stable speed by adapting the difference in velocity of each motor-wheel according to the direction in the case of a turn. Two types of controllers are employed by a hybrid control scheme to assure the control and the performance of the vehicle. This hybrid control scheme guarantees the stability of the vehicle by ED, reduces the chattering phenomena in the PMSM electric motor, and improves the disturbance rejection ability which employs tow types of controllers. The neuro-fuzzy sliding mode control on the direct current loop and ESO controller on the speed loop, and the quadratic current loop; taking into account the dynamic of the vehicle. Simulation runs under Matlab/Simulink to assess the efficiency, and strength of the recommended control method on the closed loop system.
La revue : Energy
Domaine : Electrical Engineering
Mots Clés : Electric vehicleDynamicPMSMNeuro-fuzzy sliding mode controlExtended state observer ESO
Auteur : I. F.Bouguenna, A.Azaiz, A. Tahour
Issn : 0360-5442 Eissn : vol : 169, Num : 169, pp : 1054-1063
Date de publication : 2019-02-15
Résume : The choice of the control techniques has a positive impact on the traction chain particularly disturbance rejection ability and the energy management in the electric vehicle (electric motor, inverter, transmission, ect.). In this paper, a robust neuro-fuzzy-sliding mode control (RNFSMC) with extended state observer (ESO) technique is applied on the traction chain of the electric vehicle (Permanent magnet synchronous motor PMSM, Inverter, Transmission). However, most of the existing strategies of control that are applied on the traction chain lead to chattering phenomena, reducing the electric motor performance and disturbance rejection ability without forgetting the bad energy management on board the electric vehicle. To further enhance the performance of the traction chain, a hybrid control scheme is used to severally decrease the chattering phenomena in the PMSM electric motor and evolve the disturbance rejection ability which employs two types of controllers: Neuro-fuzzy sliding mode control on the direct current loop and ESO controller on both speed, and quadrature current loops taking into account the dynamic of the vehicle. Simulations by Matlab/Simulink are used to indicate the validity of the planed scheme on the closed-loop system. The simulation results show the effectiveness of the proposed control strategy with desired tracking accuracy.
