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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) Journal of Robotics and Control (JRC) International Journal of Robotics and Control Systems
Tayane, Souad
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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Synchronous Reluctance Motor Performance Improvement Using MTPA Control Strategy and Five-Level Inverter Topology Zahraoui, Yassine; Moutchou, Mohamed; Tayane, Souad; Fahassa, Chaymae; Elbadaoui, Sara; Ma'arif, Alfian
Journal of Robotics and Control (JRC) Vol 3, No 5 (2022): September
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i5.15326

Abstract

An improved vector control method is presented in this study to enhance synchronous reluctance motor (SynRM) performance. The maximum torque per ampere (MTPA) technique has demonstrated good dynamic properties since the torque control is closely tied to the current control. The selection of the control approach is primarily influenced by how the reference current values will be defined. Additionally, a five-level neutral-point-clamped (NPC) inverter replaces the traditional two-level inverter. Only eight voltage vectors can be produced by a two-level inverter, whereas one hundred twenty-five voltage vectors can be generated by a five-level inverter. The goal is to produce an output voltage vector that closely resembles the reference voltage vector in order to ensure a quick response on the one hand and enhance dynamic performance on the other. An exact comparison of the suggested vector control strategy's properties is made once it has been simulated in MATLAB/Simulink. The acquired findings are satisfactory and high performance is attained in terms of response time, torque ripple reduction, and current waveform improvement.
Hybrid fuel cell-supercapacitor system: modeling and energy management using Proteus Haidoury, Mohamed; Rachidi, Mohammed; El Hadraoui, Hicham; Laayatii, Oussama; Kourab, Zakaria; Tayane, Souad; Ennaji, Mohamed
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp110-128

Abstract

The increasing adoption of electric vehicles (EVs) presents a promising solution for achieving sustainable transportation and reducing carbon emissions. To keep pace with technological advancements in the vehicular industry, this paper proposes the development of a hybrid energy storage system (HESS) and an energy management strategy (EMS) for EVs, implemented using Proteus Spice Ver 8. The HESS consists of a proton exchange membrane fuel cell (PEMFC) as the primary source and a supercapacitor (SC) as the secondary source. The EMS, integrated into an electronic board based on the STM32, utilizes a low-pass filter algorithm to distribute energy between the sources. The accuracy of the proposed PEMFC and SC models is validated by comparing Proteus simulation results with experimental tests conducted on the Bahia didactic bench and Maxwell SC bench, respectively. To optimize energy efficiency, simulations of the HESS system involve adjusting the hybridization rate through changes in the cutoff frequency. The analysis compares the state-of-charge (SOC) of the SC and the voltage efficiency of the fuel cell (FC), across different frequencies to optimize overall system performance. The results highlight that the chosen strategy satisfies the energy demand while preserving the FC’s dynamic performance and optimizing its utilization to the maximum.
Induction Motor Performance Improvement using Super Twisting SMC and Twelve Sector DTC Zahraoui, Yassine; Moutchou, Mohamed; Tayane, Souad; Fahassa, Chaymae; Elbadaoui, Sara
International Journal of Robotics and Control Systems Vol 4, No 1 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i1.1090

Abstract

Induction motor (IM) direct torque control (DTC) is prone to a number of weaknesses, including uncertainty, external disturbances, and non-linear dynamics. Hysteresis controllers are used in the inner loops of this control method, whereas traditional proportional-integral (PI) controllers are used in the outer loop. A high-performance torque and speed system is consequently needed to assure a stable and reliable command that can tolerate such unsettled effects. This paper treats the design of a robust sensorless twelve-sector DTC of a three-phase IM. The speed controller is conceived based on high-order super-twisting sliding mode control with integral action (iSTSMC). The goal is to decrease the flux, torque, the current ripples that constitute the major conventional DTC drawbacks. The phase current ripples have been effectively reduced from 76.92% to 45.30% with a difference of 31.62%. A robust adaptive flux and speed observer-based fuzzy logic mechanism are inserted to get rid of the mechanical sensor. Satisfactory results have been got through simulations in MATLAB/Simulink under load disturbance. In comparison to a conventional six-sector DTC, the suggested technique has a higher performance and lower distortion rate.
Analyzing the Flow of Injection Molding for Water Filter Handle: Filling, Packing, and Warpage Achor, Zineb; Zahraoui, Yassine; Tayane, Souad; Ennaji, Mohamed; Gaber, Jaafar
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1561

Abstract

Injection molding is a crucial manufacturing technology for producing complex, high-quality parts at scale, making it essential in various industries, including consumer electronics and automotive sectors. However, a lack of understanding about how injection parameters impact common defects like sink marks, short shots, and warpage often limits the widespread adoption of injection molding. This research aims to bridge this gap by providing a comprehensive digital simulation of the injection molding process within a complex mold cavity. Utilizing Moldex3D and the Finite Volume Method (FVM), this study characterizes essential material properties–viscosity, specific heat, density, and thermal conductivity–and examines the effects of gate location and part design on minimizing weld lines and warpage. The FVM involves dividing the computational domain into a finite number of small control volumes. This method is particularly well-suited for handling complex geometries and flow conditions, facilitating detailed and accurate simulations. This study employs Moldex3D, a leading simulation software in the field of injection molding, to demonstrate the use of CAE for design verification and process innovation. Moldex3D’s advanced capabilities make it an ideal tool for simulating injection molding processes, helping improve the quality of parts and contributing to the overall advancement of molding skills in the industry. The simulations revealed optimal gate locations that significantly improved filling patterns, reduced warpage by 50%, and minimized weld lines, thereby enhancing overall part quality. Key contributions of this research include the identification of critical flow characteristics, the reduction of defect-prone regions, and the enhancement of plastic component rigidity. This study provides valuable insights into optimizing injection molding processes, offering a pathway to improved efficiency and part quality in advanced manufacturing.
Development of a PEM fuel cell equivalent circuit model with PINN-based parameter identification Taleb, Ismail Ait; Kourab, Zakaria; Tayane, Souad; Ennaji, Mohamed; Gaber, Jaafar
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i4.pp2804-2818

Abstract

This paper presents a novel equivalent electrical circuit model for proton exchange membrane fuel cells (PEMFCs) and introduces a physics-informed neural network (PINN) algorithm for parameter identification. The proposed model provides a more accurate representation of the fuel cell’s dynamic behavior while maintaining computational efficiency. Unlike conventional methods, the PINN framework integrates physical constraints with data-driven learning, ensuring physically consistent parameter estimation. To validate its effectiveness, the proposed model is compared with the widely used RC equivalent circuit and a generic PEMFC model. Experimental data from a 1.2 kW PEMFC test bench serve as a benchmark for evaluating the transient and steady-state performance of each modeling approach. Results demonstrate that the proposed circuit, combined with PINN-based identification, yields enhanced accuracy in predicting voltage response under various operating conditions. Additionally, the model exhibits improved adaptability to transient phenomena compared to conventional equivalent circuits. These findings highlight the potential of physics-informed machine learning for advancing fuel cell modeling and control strategies.
Co-Authors Achor, Zineb Alfian Ma’arif El Hadraoui, Hicham Elbadaoui, Sara Ennaji, Mohamed Fahassa, Chaymae Gaber, Jaafar Haidoury, Mohamed Kourab, Zakaria Laayatii, Oussama Moutchou, Mohamed Rachidi, Mohammed Taleb, Ismail Ait Zahraoui, Yassine