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Performing accurate numerical simulations of electrical drives, the precise knowledge of the local magnetic material properties is of utmost importance. Due to the various manufacturing steps, e.g. heat treatment or cutting techniques, the magnetic material properties can strongly vary locally, and the assumption of homogenized global material parameters is no longer feasible. This paper aims to present the general methodology and two different solution strategies for determining the local magnetic material properties using reference and simulation data.

The general methodology combines methods based on measurement, numerical simulation and solving an inverse problem. Therefore, a sensor-actuator system is used to characterize electrical steel sheets locally. Based on the measurement data and results from the finite element simulation, the inverse problem is solved with two different solution strategies. The first one is a quasi Newton method (QNM) using Broyden's update formula to approximate the Jacobian and the second is an adjoint method. For comparison of both methods regarding convergence and efficiency, an artificial example with a linear material model is considered.

The QNM and the adjoint method show similar convergence behavior for two different cutting-edge effects. Furthermore, considering a priori information improved the convergence rate. However, no impact on the stability and the remaining error is observed.

The presented methodology enables a fast and simple determination of the local magnetic material properties of electrical steel sheets without the need for a large number of samples or special preparation procedures.

A new method for the numerical computation of the dynamic behaviour of electro‐dynamic loudspeakers is presented. The numerical scheme, based on the finite element method (FEM), allows the simulation of coupled magnetic, mechanical and acoustic fields. The obtained simulation results are in good agreement with measured data.

A major purpose of vector hysteresis models lies in the prediction of power losses under rotating magnetic fields. The well-known vector Preisach model by Mayergoyz has been shown to well predict such power losses at low amplitudes of the applied field. However, in its original form, it fails to predict the reduction of rotational power losses at high fields. In recent years, two variants of a novel vector Preisach model based on rotational operators have been published and investigated with respect to general accuracy and performance. This paper aims to examine the capabilities of the named vector Preisach models in terms of rotational hysteresis loss calculations.

In a first step, both variants of the novel rotational operator-based vector Preisach model are tested with respect to their overall capability to prescribe rotational hysteresis losses. Hereby, the direct influence of the model-specific parameters onto the computable losses is investigated. Afterward, it is researched whether there exists an optimized set of parameters for these models that allows the matching of measured rotational hysteresis losses.

The theoretical investigations on the influence of the model-specific parameters onto the computable rotational hysteresis losses showed that such losses can be predicted in general and that a variation of these parameters allows to adapt the simulated loss curves in both shape and amplitude. Furthermore, an optimized parameter set for the prediction of the named losses could be retrieved by direct matching of simulated and measured loss curves.

Even though the practical applicability and the efficiency of the novel vector Preisach model based on rotational operators has been proven in previous publications, its capabilities to predict rotational hysteresis losses has not been researched so far. This publication does not only show the general possibility to compute such losses with help of the named vector Preisach models but also in addition provides a routine to derive an optimized parameter set, which allows an accurate modeling of actually measured loss curves.

In this paper, an efficient magnetomechanical calculation scheme based on the finite element method is presented. This scheme is used for the precise forecast of the dynamical behavior of a clinical magnetic resonance imaging scanner. The validity of the computer simulations has been verified by means of appropriate measurements. Application examples include the optimization of the superconducting magnet regarding the eddy currents and vibrations in its cryostat.

A recently developed calculation scheme for the numerical computation of the load‐controlled acoustic noise of power transformers is presented. This modeling scheme allows the precise and efficient computation of the coupled electromagnetic, mechanical and acoustic fields. The equations are solved using the finite element method (FEM) as well as the boundary element method (BEM), resulting in a separation of the acoustic‐magnetomechanical calculation of the winding vibrations resp. the acoustic‐mechanical computation of the tank vibrations (using FEM) and the calculation of the acoustic free‐field radiation (using BEM). The validity of the computer simulations has been verified by means of appropriate measurements. Simulated and measured values for winding and tank surface vibrations as well as the sound power level of the loaded transformer are found to be in good agreement.

This paper presents a 2D nonlinear magnetomechanical analysis of an electromagnetic actuator based on finite elements. An impact mechanical problem with its inherent convergence problems has to be solved inside the magnetic field region. Beside material and geometric nonlinearities also dynamic effects like eddy currents are considered.

The fast and flexible development of fast switching electromagnetic valves as used in modern gasoline engine demands the availability of efficient and accurate simulation tools. The purpose of this paper is to provide an enhanced computational scheme of these actuators including all relevant physical effects of magneto‐mechanical systems and including contact mechanics.

The finite element (FE) method is applied to efficiently solve the arising coupled system of partial differential equations describing magneto‐mechanical systems. The algorithm for contact mechanics is based on the cross‐constraint method using an energy‐ and momentum‐conserving time‐discretisation scheme. Although solving separately for the electromagnetic and mechanical system, a strong coupling is ensured within each time step by an iterative process with stopping criterion.

The numerical simulations of the full switching cycle of an electromagnetic direct injection valve, including the bouncing during the closing state, are just feasible with an enhanced and robust mechanical contact algorithm. Furthermore, the solution of the nonlinear electromagnetic and mechanical equations needs a Newton scheme with a line search scheme for the relaxation of the step size.

The paper provides a numerical simulation scheme based on the FE method, which includes all relevant physical effects in magneto‐mechanical systems, and which is robust even for long‐term contact periods with multitude re‐opening phases.

Magnetostrictive alloys are widely used in actuator and sensor applications. The purpose of this paper is to developed a realistic physical model and a numerical computational scheme for their precise computation.

The main step in the physical modeling is the decomposition of the mechanical strain and the magnetic induction into a reversible and an irreversible part. For the efficient solution of the arising coupled nonlinear partial differential equations the authors apply the finite element method.

It can be demonstrated, that the hysteresis operators can be fitted by appropriate measurements. Therewith, the developed physical model and numerical simulation scheme is applicable for the design of magnetostrictive actuators and sensors.

The decomposition of the mechanical strain and the magnetic induction into a reversible and an irreversible part. The reversible part is described by the linear magnetostrictive constitutive equations, where the entries of the coupling tensor depend on the magnetization. The irreversible part of the magnetic induction is modeled by a Preisach hysteresis operator, and the irreversible part of the mechanical strain by a polynomial function depending on the magnetization.

A wide range of micro‐electro‐mechanical‐systems are based on the electrostatic principle, and for their design the computation of the electric capacities is of great importance. The purpose of this paper is to efficiently compute the capacities as a function of all possible positions of the two electrode structures within the transducer by an enhanced boundary element method (BEM).

A Galerkin BEM is developed and the arising algebraic system of equations is efficiently solved by a CG‐method with a multilevel preconditioner and an appropriate fast multipole algorithm for the matrix‐vector operations within the CG‐iterations.

It can be demonstrated that the piecewise linear and discontinuous trial functions give an approximation, which is almost as good as the one of the piecewise constant trial functions on the refined mesh, at lower computational costs and at about the same memory requirements.

The paper can proof mathematically and demonstrate in practice, that a higher order of convergence is achieved by using piecewise linear, globally discontinuous basis functions instead of piecewise constant basis functions. In addition, an appropriate preconditioner (artificial multilevel boundary element preconditioner, which is based on the Bramble Pasciak Xu like preconditioner) has been developed for the fast iterative solution of the algebraic system of equations.

The focus of this paper is on the efficient numerical computation of 3D electromagnetic field problems by using the finite element (FE) and multigrid (MG) methods. The magnetic vector potential is used as the field variable and the discretization is performed by Lagrange (nodal) as well as Ne´de´lec (edge) finite elements. The resulting system of equations is solved by applying a preconditioned conjugate gradient (PCG) method with an adapted algebraic multigrid (AMG) as well as an appropriate geometric MG preconditioner.