Artificial neural network (ANN) based fast and accurate inductor modeling and design
This paper analyzes the potential of Artificial Neural Networks (ANNs) for the modeling and
optimization of magnetic components and, specifically, inductors. After reviewing the basic …
optimization of magnetic components and, specifically, inductors. After reviewing the basic …
Surrogate-based multi-objective optimization of electrical machine designs facilitating tolerance analysis
Multi-objective optimization algorithms are becoming ever more popular in the field of
electrical machine design as they provide engineers with an automated way of efficiently …
electrical machine design as they provide engineers with an automated way of efficiently …
Fast design optimization method utilizing a combination of artificial neural networks and genetic algorithms for dynamic inductive power transfer systems
Multiple parameters with large nonlinear characteristics must be considered simultaneously
to design the coil dimensions of static inductive power transfer (SIPT) systems. The design of …
to design the coil dimensions of static inductive power transfer (SIPT) systems. The design of …
Multiobjective optimization design of small-scale wind power generator with outer rotor based on Box–Behnken design
SH Lee, YJ Kim, KS Lee, SJ Kim - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
In this paper, the finite-element method (FEM) based on 2-D numerical analysis was used
for the basic design and characteristics analysis of a small-scale 3-kW wind power generator …
for the basic design and characteristics analysis of a small-scale 3-kW wind power generator …
Conceptual framework of antecedents to trends on permanent magnet synchronous generators for wind energy conversion systems
Wind Energy Conversion System (WECS) plays an inevitable role across the world. WECS
consist of many components and equipment's such as turbines, hub assembly, yaw …
consist of many components and equipment's such as turbines, hub assembly, yaw …
Multi-attribute machine learning model for electrical motors performance prediction
Designing an electrical motor is a complex process that needs to deal with the non-linearity
phenomena caused by the saturation of the iron at high magnetic field strength, the multi …
phenomena caused by the saturation of the iron at high magnetic field strength, the multi …
A Hybrid Machine Learning Model for Efficient XML Parsing
M Ali, MA Khan, R Ur Rasool - IEEE Access, 2024 - ieeexplore.ieee.org
The Extensible Markup Language (XML) files are extensively used for representing
structured data on the web for file configuration, exchanging data between distinct …
structured data on the web for file configuration, exchanging data between distinct …
Optimization of instantaneous torque shape of PM motors using artificial neural networks based on FE results
A method that combines artificial neural networks (ANN) and finite-elements method is
introduced to estimate the instantaneous torque of two classes of permanent magnet motors …
introduced to estimate the instantaneous torque of two classes of permanent magnet motors …
Grid connected variable speed wind turbine modeling, dynamic performance and control
AE Haniotis, KS Soutis, AG Kladas… - IEEE PES Power …, 2004 - ieeexplore.ieee.org
In this paper the electrical part of a grid connected variable speed wind turbine is
considered, equipped with a permanent magnet synchronous generator. The modeling of …
considered, equipped with a permanent magnet synchronous generator. The modeling of …
Sensitivity Analysis of Parameters Affecting the Performance of Radial Flux Low-Speed PMSG
This paper is committed to build a comprehensive understanding of the different design
possibilities, working closely with inner-rotor, radial-flux, permanent magnet synchronous …
possibilities, working closely with inner-rotor, radial-flux, permanent magnet synchronous …