Oumaymah ELAMRI

Dr. Oumaymah ELAMRI

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 April 2025 in Brazilian Journal of Physics
Verified
Journal Article
Closed access
PDF file
JWJacob Wekalao
Jacob Wekalao
SNStephen Maina Njoroge
Stephen Maina Njoroge
OEOumaymah ELAMRI
Oumaymah ELAMRI



25 February 2020 in International Journal of Engineering Trends and Technology
Verified
Journal Article
Closed access
Alla Eddine Toubal MaamarAlla Eddine Toubal Maamar
Alla Eddine Toubal Maamar
MHM’hamed Helaimi
M’hamed Helaimi
RTRachid Taleb
Rachid Taleb
HMHadj Mouloudj
Hadj Mouloudj
OEOumaymah ELAMRI
Oumaymah ELAMRI
AGAbdelatif Gadoum
Abdelatif Gadoum
Mathematical Analysis of N-R Algorithm for Experimental Implementation of SHEPWM Control on Single-phase Inverter

1 December 2020 in Advances in Science, Technology and Engineering Systems Journal
Verified
Journal Article
Open access
OEOumaymah ELAMRI
Oumaymah ELAMRI
OAOukassi Abdellah
Oukassi Abdellah
BOBouhali Omar
Bouhali Omar
ELEl Bahir Lhoussain
El Bahir Lhoussain

15 April 2024 in Mathematical Problems in Engineering
Verified
Journal Article
Open access
PDF file
*O*abdellah Oukassi
*abdellah Oukassi
OEOumaymah ELAMRI
Oumaymah ELAMRI
ZBZakaria Boulghasoul
Zakaria Boulghasoul
This paper offers a system for an electric vehicle. It consists of digitally controlling an induction motor without using a speed sensor. The machine is powered by a five-level cascading H-bridge inverter. The SVM control principle is used to manage the status of the five-level inverter; this removes harmonics. The H-bridge inverter converter is powered by photovoltaic sources via a serial converter, using the maximum power point tracker control principle. This structure can also reduce shading losses. In the absence of a mechanical sensor, a dynamic model of the asynchronous machine is utilized with the state variables defined in the stator reference frame. The state vector consists of the components of the rotor flux and stator current. The article provides a comparison of two methods widely used on an induction motor drive. The adaptive model-reference system method and Luenberger observer are evaluated using an active control strategy to reject disturbances to minimize the impact of disturbances. The operating principles of each method are described, and the mathematical models of training systems are developed. Both methods provide a promise for high-speed estimate applications in simulation environments. The simulation results obtained show the correct operation of both observers. Perfect decoupling between the velocity and flow control loops is observed, taking into account any disturbances that may affect the system.