<span lang="EN-US">Electrical machines lifetime and performances could be improved when along the design process both electromagnetic and thermal behaviors are taken into account. Moreover, real time information about the device thermal state is necessary to an appropriate control with minimized losses. Models based on lumped parameter thermal circuits are: generic, rapid, accurate and qualified as a convenient solution for power systems. The purpose of the present paper is to validate a simulation platform intended for the prediction of the thermal state of an induction motor covering all operation regimes. To do so, in steady state, the proposed model is validated using finite element calculation and experimental records. Then, in an overload situation, obtained temperatures are compared to finite element’s ones. It has been found that, in both regimes, simulation results are with closed proximity to finite element’s ones and experimental records.</span>
This paper presents an original and autonomous solar pumping system, based on a Switched Reluctance Motor commutated by photovoltaic cells (SRMPV) and powered by a photovoltaic generator. In this work, experimental tests characterizing the SRMPV are presented. Based on these experiments, the first mathematical model of this complex system is developed and implemented under the Matlab-Simulink platform. In order to optimize the design of the SRMPV, the simulation platform is used to perform a sensitivity study. This research will focus on the determination of the optimal number of coils, the optimal air gap, and the optimal winding cross area of the switched reluctance motor.
This paper proposes a fast and accurate optimal sizing design of 1.5 MW Permanent Magnets Synchronous Generator (PMSG) for a grid-connected wind application. A design strategy inspired from the output space mapping technique is adopted. A fast analytical model is used and detailed to determine the parameters and the performances of the PMSG. Then, the results are validated by a precise finite element model and adjusted iteratively until coherence between the two models is obtained. A multi-objective particle swarm optimization algorithm is deployed with aim of reducing the total losses and weight of the generator. The algorithm's parameters and results are given and analyzed. Three optimal machines are chosen and tested using a 2D-finite element model. The main design parameters of the optimal generators are given and discussed. Good efficiency and optimal designs are obtained for the sized machines thanks to the adopted design strategy.
The present work aims to improve the traction chain system of a leisure electric vehicle equipped with a Li-S battery. For that, an equivalent circuit model of the battery was developed and implanted in the traction chain model in order to investigate the autonomy of the electric vehicle under different drive-cycles. The obtained results show a good quality of the studied vehicle in terms of autonomy and energy consumption.
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