http://hdl.handle.net/STDB_UNAM/192 Wed, 15 Apr 2026 23:06:52 GMT 2026-04-15T23:06:52Z http://hdl.handle.net/STDB_UNAM/521 MPPT Technique Based on Neural Network for Photovoltaic System Elhor, Abderrahmane The using of an efficient MPPT (Maximum Power Point Tracking) algorithm influences a lot in the global efficiency of the PV system. This thesis presents a detailed study based on simulation of different MPPT algorithms with their features using two systems (off-grid and on-grid). The off-grid system contains a PV array connected to a boost converter and a resistive load. On the off-grid system a simulation is presented using MATLAB/SIMULINK platform with several MPPT algorithms. The simulated MPPT algorithms are the conventionals Incremental Conductance (IncCond), Perturb and Observe (P&O), Open Circuit Voltage (OCV) and a new developed Neural Network (NN) under different environmental conditions of temperature and irradiance. As a result of the simulation, the NN algorithm has a quick response, i.e, it requires less time to reach the MPP and high efficiency and less oscillation comparing with the conventional methods. On the other hand, a single-phase two-stage photovoltaic grid-connected system is simulated which contains a PV array, a boost converter, a dc link capacitor, an inverter, an output L filter and the utility grid. In that system a control of dc link voltage, the injected current and the MPPT is made. Another MPPT algorithm based on NN (modifiedNN) was also established. Showed later that is the most suitable for the system. The maximum of power is achieved when the irradiance is maximal and the temperature is minimal. Finally, a study of the influence of the variation in the climatic conditions on the output performance of the system is done. Fri, 01 Jan 2021 00:00:00 GMT http://hdl.handle.net/STDB_UNAM/521 2021-01-01T00:00:00Z http://hdl.handle.net/STDB_UNAM/252 Gestion intelligente de charge et de décharge de batteries pour un système photovoltaïque relié au réseau. BENTRAR, Mohamed; CHAOUCHE, Hibet Errahmen Ce mémoire est consacré à une technique de gestion de charge et de décharge de batteries dans un système photovoltaïque relié au réseau. Ladite technique consiste à choisir entre deux stratégies de gestion de stockage : la première se limite à écrêter des pics de consommation lorsque la production d'énergie photovoltaïque est faible et n'arrive pas à couvrir la charge électrique, alors que la seconde, appliquée lorsque la production de l'énergie photovoltaïque est abondante, vise à adopter des pro ls de décharge adaptés aux restrictions de charge et décharge des batteries a n d'éviter leur endommagement rapide. La gestion intelligente de charge et de décharge des batteries permet d'assurer une longue durée de vie des batteries et une bonne exploitation de l'énergie produite par le générateur photovoltaïque et même à vendre l’excès d'énergie au réseau. Mon, 27 Sep 2021 00:00:00 GMT http://hdl.handle.net/STDB_UNAM/252 2021-09-27T00:00:00Z http://hdl.handle.net/STDB_UNAM/246 Optimizing the magnetic heat exchangers of thermomagnetic motors: A heat transfer study SAOUD, ROUMAISSA This work explored the optimization procedures of heat ex- changers to be used in thermomagnetic motors. The article main focus is the use of CFD simulations to maximize the heat exchange rate between the magnetic materials and the hot and cold fluids. This is done in order to have the maximum possible operational frequency in thermomagnetic motors. This was accomplished by optimizing the geometries of the channels of the heat exchangers. As the focus of this work was to improve the thermo- magnetic heat exchangers geometrically, some important characteristics were observed. First of all, taking into account the fact that the heat transfer rate is highly influenced by the contact area between the fluid and the plate, and that the length of the plate is constant and depends on constructive characteristics of the motor, we have that, in order to improve the heat transfer speed, the perimeter of the channels must be increased. In this work only channels having convex cross section formats were considered, but the use of channels with concave cross section may lead to higher contact areas and therefore improve even more the heat transfer rate. Another very important aspect is that the temperature gradient along the plate needs also to be taken into account, because the magnetic force distribution applied on the plates is perpendicular to its linear displacement, so this gradient can lead to some misalignment of the force on the plates leading to the blockage of the motor; in this sense we showed that the best option to maximize the temperature homogeneity is the use of a non-uniform cross section in the channels. Future works shall be developed considering the real properties of the magneto-caloric materials for the simulations, which will allow the use of the CFD simulations together with magnetic simulations to determine the dynamics of thermomagnetic motors and also their efficiencies. Wed, 29 Sep 2021 00:00:00 GMT http://hdl.handle.net/STDB_UNAM/246 2021-09-29T00:00:00Z http://hdl.handle.net/STDB_UNAM/244 Energy Management of Li-Po Batteries in the Mobile Robotics Domain. Chellal, Arezki Abderrahim The importance of energy storage continues to grow, whether in power generation, consumer electronics, aviation, or other systems. Therefore, energy management in batteries is becoming an increasingly crucial aspect of optimizing the overall system and must be done properly. Very few works have been found in the literature proposing the implementation of algorithms such as EKF to predict the SOC in small systems such as mobile robots, where computational power in some application is severely lacking. To this end, this work proposes an implementation of two algorithms mainly reported in the literature for SOC estimation, in an ATMEGA328P microcontroller-based BMS, this embedded system is designed taking into consideration the criteria already defined for such a system and adding the aspect of flexibility and ease of implementation. One of the implemented algorithms performs the prediction, while the other will be responsible for the monitoring. Fri, 01 Jan 2021 00:00:00 GMT http://hdl.handle.net/STDB_UNAM/244 2021-01-01T00:00:00Z