Conference Agenda

The determination of the natural frequencies for graphene finite structures is realized in the present work using a finite-difference scheme. The frequency-dispersive two-dimensional material is treated as an equivalent surface current density, while an appropriate auxiliary differential equation is introduced to acquire a linear eigenvalue problem. Then, the finite-difference discretization is performed in a Yee-cell manner to straightforwardly implement all the required curl operations. Finally, a rectangular graphene patch is employed to validate the proposed methodology. The numerically extracted eigenstates verified the precise modeling via the successful comparison to the well-established resonator scattering approach.

A B-conforming time stepping volume integral formulation (VIM) for nonlinear 3D field-circuit coupled problems is presented in this paper. The advantage of the VIM with respect to the finite element method (FEM) is that only the ferromagnetic regions have to be discretized, thus avoiding to mesh the air. It is an appealing approach because it avoids the numerical errors that can arise from modeling the air. An application to a current transformer is presented and compared to the FEM to validate its accuracy.

In numerous problems with arbitrary wire configurations, e.g. in power electronics, neither the skin effect, the proximity effect nor parasitic capacitances can be neglected. Finite element modeling in this context may become rather expensive or practically improper. To this end, a novel two-domain method has been developed, which uses a usual finite element approximation outside of wire volumes and a problem specific approach on the inside. Numerical simulations of small examples show very satisfactory results.

If a boundary-value problem is discretized with the extended Element-Free Galerkin (EFG) method, an asymmetric EFG-type Saddle-Point (EFG-SP) problem is obtained and it is known as a linear system that is difficult to solve numerically. In the present study, the Asymmetric-version improved Variable-Reduction Method (AiVRM) is proposed as a solver of the problem and its performance is investigated numerically. Consequently, it is found that, especially for a large-scale asymmetric EFG-SP problem, the AiVRM is more effective than the preconditioned Krylov subspace method.

Electrohydraulic servovalves used in various aircraft systems (flight control system, auxiliary power unit, etc.) are a key element in fluid flow and pressure control. This paper presents a 3D analytical modelling method of the servovalves torque motor electromagnetic performance. This analytical model, based on a reluctance network, allows actuator performance to be quickly evaluated taking into account the complex 3D geometry and the high flux leakage rate.

Although MUltiple SIgnal Classification (MUSIC) has shown its feasibility as a non-iterative technique in microwave imaging for identifying small anomalies, a priori information of background medium such as permittivity, conductivity, etc., must be known. In this contribution, we apply MUSIC when material properties of the background are unknown and theoretically explain why inaccurate results are appear. Simulation results using synthetic data are exhibited to support theoretical result.

The penetration of a time-varying magnetic field in electrically conductive buried permanent magnets of synchronous machines induces a current density which in turn leads to an additional loss power and a potential heat source. The enclosing rotor steel laminations do not shield the permanent magnets due to their too low conductivity and permeability. The amplitude of the magnetic flux density pulsations depends on the specific toplogy of the electrical machine. The accurate calculation of the eddy current losses holds a large computational effort. However, the evaluation of the frequency distribution of occuring flux density pulsations is an efficient approach to study the presence of eddy current losses qualitatively. The aim of this work is to study flux density pulsations as a measure for the related eddy current losses for different arrangements of permanent magnets in the rotor and their vicinity towards the air gap.

The study of superconductive tapes requires special- ized formulations in order to account for the high aspect ratio of the tapes as well as the extremely high conductivity of the superconductive layer. This papers presents a new formulation coupling the line integral of the magnetic vector potential defined in the whole domain and the stream function defined on the nodes of the superconductive layer.

Permanent magnet-free electrical machines like synchronous reluctance motors (SynRM) are becoming more popular for financial and environmental reasons. The SynRMs are operated at a heavily non-linear state; thus, the linearisation used for the representation in direct (d) and quadrature (q) coordinate system yield inaccurate results. An effective current injection control algorithm can decrease the torque ripple and vibration and improve the power factor of SynRM. The differential inductance values are required to extend the algorithm to the non-linear domain. This paper defines the resolution of these inductance maps along their parameters by a co-energy-based force calculation for constant current and extends to the synchronous operation mode. The expected outcome is a direct torque-current relation for non-linear saturated machines, such as synchronous reluctance motors, calculated by Finite Element Analysis. The additional benefits are more accurate torque calculation with faster computational speed.

Digitalization is a major driving force behind the development of new calculation methods. Computationally efficient digital twins are often created by reducing the complexity of existing models – such as numerical electromagnetic field analysis – for a certain narrow target area. Mapping the causal correlations during the complex modeling – in the field computation and coupled problems – and maintaining and verifying the causal correlations during the model reduction process is of paramount importance. The proposed Causal Correlation Fingerprinting is the graphical representation of the correlation matrix from Uncertainty Quantification and the Causality Analysis of the resulting dataset to focus it on the causally relevant data. The paper presents this powerful visual tool and how it is capable to characterize the behavior of “black box type” numerical and simplified models qualitatively. It allows easy interpretation and deeper insight and enables a straightforward comparison of complex and simplified models as it is demonstrated in the paper.

This paper presents a novel topology optimization method for electrical machines, where a QUBO-type surrogate model is constructed using analytical data obtained offline. Moreover, quantum annealing is utilized to enhance the convergence of the optimization. Since the proposed method can be used to reduce the number of inferior solutions in the optimization, convergence of the optimization can be improved. In this study, the proposed method is applied to an optimization problem of the magnetic head to validate the effectiveness. From the numerical results, it can be confirmed that the proposed method can enhance convergence of optimization without increasing computational costs.