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Bearingless drives integrate the functionality of magnetic bearings and an electric machine into a single device. While this integration allows very compact drives offering all advantages of magnetic levitation, the design process becomes significantly more complex. This work deals with the numerous topological and geometric design decisions which need to be taken for such a bearingless drive. Additionally, the definition of suitable optimization targets for the electromagnetic simulation process is outlined. The proposed guidelines generate a complex relationship of different dependencies which is then fed into the MagOpt optimizer for the design of a high speed bearingless disk drive, which allows verifying the optimization results through measurement results from two prototype drives. [ABSTRACT FROM AUTHOR]

This paper deals with accelerating typical optimization scenarios for electrical machine designs. Besides the advantage of a reduced computation time, this leads to a reduction in computational power and thus to a lower power consumption when running the optimization. If machines of high power density are required, usually highly utilized assemblies that feature nonlinear characteristics are obtained. Optimization scenarios are considered where the evaluation of a potential design requires computationally expensive nonlinear finite element (FE) simulations. Improving the speed of optimization runs takes top priority and various measures can be considered. This paper is about basic and easily achievable measures, and techniques for a time-wise and computationally efficient exploration of the design space. Suggested improvements comprise sophisticated emerging techniques for modeling machine characteristics by paring the number of required FE simulations down to the minimum and nonlinear modeling of the targets of the optimization scenario as functions of the design parameters to further reduce the number of FE evaluations. In the case study, the analysis of a typical optimization task is given, and achievable speed improvements as well as still present issues are discussed. [ABSTRACT FROM AUTHOR]

Optimizing mechatronic components is of increasing importance, e.g. for minimizing energy consumption and the use of rare materials. MagOpt is a modular software tool for the simulation and optimization of mechatronic components. Parametric design optimization can be carried out with various different optimization strategies like gradient-based methods or multi-objective evolutionary or genetic algorithms. MagOpt features a flexible structure for the storage of complex data and an open and modular interface to existing third-party programs. One such third-party program which can be used by MagOpt for the optimization of mechanic components is the multi-body software HOTINT. This article describes MagOpt and how it was coupled with HOTINT to optimize a rotor geometry. [ABSTRACT FROM AUTHOR]