496 research outputs found
Effect of transmitter position on the torque generation of a magnetic resonance based motoring system
Strongly coupled magnetic resonance is most often used to transfer electrical power from a transmitter to a resonant receiver coil to supply devices over an air gap. In this work, the induced current in two receiver coils (stator and rotor) is used to generate torque on the rotor coil. The effect of the transmitter position relative to the stator and rotor receiver coils on the torque generation is studied in detail, both in simulation and experimentally. Results show a 36% to 37% gain in peak torque when properly varying the stator orientation for a given transmitter distance
Effect of stator slot openings in axial flux permanent magnet machines
The width of the stator slot openings near the air gap has a large influence on the power loss in the stator core and in the permanent magnets of axial flux permanent magnet synchronous machines. On the one hand, the increase in stator slot openings results in lower power loss in the stator iron. On the other hand, it also results in increased loss in the permanent magnets. Also the torque is reduced for large but also for very small slot openings. This paper deals with axial flux machines of the YASA type: yokeless and segmented armature. It is shown that the slot openings contribute to an unequal flux density level over the different laminations in the stator core. The effect on the power loss and the flux distribution is shown
Effect of magnetic material degradation on the optimal design parameters of electromagnetic devices
Stochastic modeling error reduction using Bayesian approach coupled with an adaptive Kriging based model
Purpose - Magnetic material properties of an electromagnetic device (EMD) can be recovered by solving a coupled experimental numerical inverse problem. In order to ensure the highest possible accuracy of the inverse problem solution, all physics of the EMD need to be perfectly modeled using a complex numerical model. However, these fine models demand a high computational time. Alternatively, less accurate coarse models can be used with a demerit of the high expected recovery errors. The purpose of this paper is to present an efficient methodology to reduce the effect of stochastic modeling errors in the inverse problem solution.
Design/methodology/approach - The recovery error in the electromagnetic inverse problem solution is reduced using the Bayesian approximation error approach coupled with an adaptive Kriging-based model. The accuracy of the forward model is assessed and adapted a priori using the cross-validation technique.
Findings - The adaptive Kriging-based model seems to be an efficient technique for modeling EMDs used in inverse problems. Moreover, using the proposed methodology, the recovery error in the electromagnetic inverse problem solution is largely reduced in a relatively small computational time and memory storage.
Originality/value - The proposed methodology is capable of not only improving the accuracy of the inverse problem solution, but also reducing the computational time as well as the memory storage. Furthermore, to the best of the authors knowledge, it is the first time to combine the adaptive Kriging-based model with the Bayesian approximation error approach for the stochastic modeling error reduction
A Rogowski-Chattock coil : sources of error
The local magnetic field is measured by means of magnetic sensors, such as a Rogowski-Chattock coil. The main advantage of the Rogowski coil is its capability to measure the field strength directly at the sample surface because both ends of the coil can be installed very close to the specimen surface. However, the measurements are affected by numerous errors, which are comprehensively discussed in this paper
Voltage sources in 2D fourier-based analytical models of electric machines
The importance of extensive optimizations during the design of electric machines entails a need for fast and accurate simulation tools. For that reason, Fourier-based analytical models have gained a lot of popularity. The problem, however, is that these models typically require a current density as input. This is in contrast with the fact that the great majority of modern drive trains are powered with the help of a pulse-width modulated voltage-source inverter. To overcome that mismatch, this paper presents a coupling of classical Fourier-based models with the equation for the terminal voltage of an electric machine, a technique that is well known in finite-element modeling but has not yet been translated to Fourier-based analytical models. Both a very general discussion of the technique and a specific example are discussed. The presented work is validated with the help of a finite-element model. A very good accuracy is obtained
Torque and torque components in high-speed permanent-magnet synchronous machines with a shielding cylinder
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Computational analysis of the effect of superparamagnetic nanoparticle properties on bioheat transfer in magnetic nanoparticle hyperthermia
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Coupled electrical-thermal model for monopolar and bipolar radiofrequency liver tumor ablation
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