Facultad de Ingeniería

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http://repositorio.unab.cl//handle/ria/2072

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Examinando Facultad de Ingeniería por Autor "Abdelrahem, Mohamed"

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    Electrostatically Doped Junctionless Graphene Nanoribbon Tunnel Field-Effect Transistor for High-Performance Gas Sensing Applications: Leveraging Doping Gates for Multi-Gas Detection
    (MDPI, 2024-04-04) Tamersit, Khalil; Kouzou, Abdellah; Rodriguez, José; Abdelrahem, Mohamed
    In this paper, a new junctionless graphene nanoribbon tunnel field-effect transistor (JLGNR TFET) is proposed as a multi-gas nanosensor. The nanosensor has been computationally assessed using a quantum simulation based on the self-consistent solutions of the mode space non-equilibrium Green’s function (NEGF) formalism coupled with the Poisson’s equation considering ballistic transport conditions. The proposed multi-gas nanosensor is endowed with two top gates ensuring both reservoirs’ doping and multi-gas sensing. The investigations have included the IDS-VGS transfer characteristics, the gas-induced electrostatic modulations, subthreshold swing, and sensitivity. The order of change in drain current has been considered as a sensitivity metric. The underlying physics of the proposed JLGNR TFET-based multi-gas nanosensor has also been studied through the analysis of the band diagrams behavior and the energy-position-resolved current spectrum. It has been found that the gas-induced work function modulation of the source (drain) gate affects the n-type (p-type) conduction branch by modulating the band-to-band tunneling (BTBT) while the p-type (n-type) conduction branch still unaffected forming a kind of high selectivity from operating regime point of view. The high sensitivity has been recorded in subthermionic subthreshold swing (SS < 60 mV/dec) regime considering small gas-induced gate work function modulation. In addition, advanced simulations have been performed for the detection of two different types of gases separately and simultaneously, where high-performance has been recorded in terms of sensitivity, selectivity, and electrical behavior. The proposed detection approach, which is viable, innovative, simple, and efficient, can be applied using other types of junctionless tunneling field-effect transistors with emerging channel nanomaterials such as the transition metal dichalcogenides materials. The proposed JLGNRTFET-based multi-gas nanosensor is not limited to two specific gases but can also detect other gases by employing appropriate gate materials in terms of selectivity.
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    Latest Advances of Model Predictive Control in Electrical Drives - Part I: Basic Concepts and Advanced Strategies
    (Institute of Electrical and Electronics Engineers Inc., 2022-04-01) Rodriguez, Jose; Garcia, Cristian; Mora, Andres; Flores-Bahamonde, Freddy; Acuna, Pablo; Novak, Mateja; Zhang, Yongchang; Tarisciotti, Luca; Davari, S. Alireza; Zhang, Zhenbin; Wang, Fengxiang; Norambuena, Margarita; Dragicevic, Tomislav; Blaabjerg, Frede; Geyer, Tobias; Kennel, Ralph; Khaburi, Davood Arab; Abdelrahem, Mohamed; Zhang, Zhen; Mijatovic, Nenad; Aguilera, Ricardo P.
    The application of model predictive control in electrical drives has been studied extensively in the past decade. This article presents what the authors consider the most relevant contributions published in the last years, mainly focusing on three relevant issues: weighting factor calculation when multiple objectives are utilized in the cost function, current/torque harmonic distortion optimization when the power converter switching frequency is reduced, and robustness improvement under parameters uncertainties. Therefore, this article aims to enable readers to have a more precise overview while facilitating their future research work in this exciting area.
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    Latest Advances of Model Predictive Control in Electrical Drives - Part II: Applications and Benchmarking With Classical Control Methods
    (Institute of Electrical and Electronics Engineers Inc., 2022-05-01) Rodriguez, Jose; Garcia, Cristian; Mora, Andres; Davari, S. Alireza; Rodas, Jorge; Valencia, Diego Fernando; Elmorshedy, Mahmoud; Wang, Fengxiang; Zuo, Kunkun; Tarisciotti, Luca; Flores-Bahamonde, Freddy; Xu, Wei; Zhang, Zhenbin; Zhang, Yongchang; Norambuena, Margarita; Emadi, Ali; Geyer, Tobias; Kennel, Ralph; Dragicevic, Tomislav; Khaburi, Davood Arab; Zhang, Zhen; Abdelrahem, Mohamed; Mijatovic, Nenad
    This article presents the application of model predictive control (MPC) in high-performance drives. A wide variety of machines have been considered: Induction machines, synchronous machines, linear motors, switched reluctance motors, and multiphase machines. The control of these machines has been done by introducing minor and easy-to-understand modifications to the basic predictive control concept, showing the high flexibility and simplicity of the strategy. The second part of the article is dedicated to the performance comparison of MPC with classical control techniques such as field-oriented control and direct torque control. The comparison considers the dynamic behavior of the drive and steady-state performance metrics, such as inverter losses, current distortion in the motor, and acoustic noise. The main conclusion is that MPC is very competitive concerning classic control methods by reducing the inverter losses and the current distortion with comparable acoustic noise.
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    Low sensitivity predictive control for doubly-fed induction generators based wind turbine applications
    (MDPI, 2021) Abdelrahem, Mohamed; Hackl, Christoph; Kennel, Ralph; Rodriguez, Jose
    In this paper, a deadbeat predictive control (DBPC) technique for doubly-fed induction generators (DFIGs) in wind turbine applications is proposed. The major features of DBPC scheme are its quick dynamic performance and its fixed switching frequency. However, the basic concept of DBPC is computing the reference voltage for the next sample from the mathematical model of the generator. Therefore, the DBPC is highly sensitive to variations of the parameters of the DFIG. To reduce this sensitivity, a disturbance observer is designed in this paper to improve the robustness of the proposed DBPC scheme. The proposed observer is very simple and easy to be implemented in real-time applications. The proposed DBPC strategy is implemented in the laboratory. Several experiments are performed with and without mismatches in the DFIG parameters. The experimental results proved the superiority of the proposed DBPC strategy over the traditional DBPC technique.