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High resolution simulations of body-internal electric field strengths induced by magneto-quasistatic fields from wireless power transfer systems are computationally expensive. The exposure simulation can be split into two separate simulation steps allowing the calculation of the magnetic flux density distribution, which serves as input into the second simulation step to calculate the body-internal electric fields. In this work, the magnetic flux density is interpolated from in situ measurements in combination with the scalar-potential finite difference scheme to calculate the resulting body-internal field. These calculations are supposed to take less than 5 s to achieve a near real-time visualization of these fields on mobile devices. The purpose of this work is to present an implementation of the simulation on graphics processing units (GPUs), allowing for the calculation of the body-internal field strength in about 3 s.

This work uses the co-simulation scalar-potential finite difference scheme to determine the body-internal electric field strength of human models with a voxel resolution of 2 × 2 × 2 mm³. The scheme is implemented on GPUs. This simulation scheme requires the magnetic flux density distribution as input, determined from radial basis functions.

Using NVIDIA A100 GPUs, the body-internal electric field strength with high-resolution models and 8.9 million degrees of freedom can be determined in about 2.3 s.

This paper describes in detail the used scheme and its implementation to make use of the computational performance of modern GPUs.

This paper aims to present a fast and modular framework implementation for the thermal analyses of foreign metal objects in the context of wireless power transfer (WPT) to evaluate whether they pose a hazard to the system. This framework serves as a decision-making tool for determining the necessity of foreign object detection in certain applications and at certain transmitted power levels.

To assess the necessity of implementing foreign object detection, the considered WPT system is modeled, and Arnoldi-Krylov-based model order reduction is applied to generate separate reduced models of the ground and vehicle modules of the WPT system. This enables interoperable evaluations to be conducted. Further discussion on the implementation details of the system-level simulations used to evaluate the electrical and thermal characteristics is provided. The resulting modular implementation allows for efficient evaluation of the thermal behavior of the wireless charging system at various transferred power levels and under various boundary conditions.

Based on the transferred power level, the WPT model, the relative positioning between the vehicle and the charging pad and the charging time, it may be necessary to divide the area of the charging pad into multiple regions for the purpose of implementing foreign object detection.

While the tools and fundamentals of thermal analysis are widely known and used, their application to high-power WPT systems for electric vehicles has not yet been thoroughly discussed in this form in the literature. The approach presented in this paper is not limited to the specific WPT model discussed but rather is directly applicable to other WPT models as well.

Inductive charging systems for electrically powered cars produce a magneto-quasistatic field and organism in the vicinity might be exposed to that field. Magneto-quasistatic fields induce electric fields in the human body that should not exceed limits given by the International Commission of Non-Ionizing Radiation protection (ICNIRP) to ensure that no harm is done to the human body. As these electric fields cannot be measured directly, they need to be derived from the measured magnetic flux densities. To get an almost real-time estimation of the harmfulness of the magnetic flux density to the human body, the electric field needs to be calculated within a minimal computing time. The purpose of this study is to identify fast linear equations solver for the discrete Poisson system of the Co-Simulation Scalar Potential Finite Difference scheme on different graphics processing unit systems.

The determination of the exposure requires a fast linear equations solver for the discrete Poisson system of the Co-Simulation Scalar Potential Finite Difference (Co-Sim. SPFD) scheme. Here, the use of the AmgX library on NVIDIA GPUs is presented for this task.

Using the AmgX library enables solving the equation system resulting from an ICNIRP recommended human voxel model resolution of 2 mm in less than 0.5 s on a single NVIDIA Tesla V100 GPU.

This work is one essential advancement to determine the exposure of humans from wireless charging system in near real-time from in situ magnetic flux density measurements.

The purpose of this paper is to describe the derivation of an adjustment directive for the non‐linear and coupled forces of a high‐comfort elevator guiding system based on so‐called electromagnetic ω‐actuators.

The derivation of the adjustment directive contains a coordinate transformation from local forces and torques to global quantities.

It is demonstrated that the derived system is able to operate the guiding system of the elevator car. Measurement results show a well running system in face of several mutual influences on the actuating forces.

The results presented offer the opportunity to increase the riding comfort and decrease the deterioration of high‐speed elevator systems. It is possible to apply the proposed system to ropeless elevators and to conventional elevator systems as well.

The methods developed and proved in this paper grant an effective way to control magnetically levitated systems with complex actuator topologies.

A fundamental disadvantage of three‐dimensional finite element (FE) simulations is high computational cost when compared to two‐dimensional models. The purpose of this paper is to present an approach to minimize the computation time by achieving the same simulation accuracy.

The applied approach for avoiding high computational cost is the multi‐slice method. This paper presents the adoption of this method to a tubular linear motor.

It is demonstrated that the multi‐slice method is applicable for tubular linear motors. Furthermore, the number of slices and thereby computation time is minimized at the same accuracy of the simulation results.

The results of this paper offer a faster computation of skewed linear motors. At this juncture, the results are independent from the deployed FE solver.

The methods developed and proved permit a faster and more accurate design of tubular linear motors.