Universität Stuttgart

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    Additively manufactured transverse flux machine components with integrated slits for loss reduction
    (2022) Kresse, Thomas; Schurr, Julian; Lanz, Maximilian; Kunert, Torsten; Schmid, Martin; Parspour, Nejila; Schneider, Gerhard; Goll, Dagmar
    Laser powder bed fusion (L-PBF) was used to produce stator half-shells of a transverse flux machine from pure iron (99.9% Fe). In order to reduce iron losses in the bulk components, radially extending slits with a nominal width of 150 and 300 µm, respectively, were integrated during manufacturing. The components were subjected to a suitable heat treatment. In addition to a microscopic examination of the slit quality, the iron losses were also measured using both a commercial and a self-developed measurement setup. The investigations showed the iron losses can be reduced by up to 49% due to the integrated slits and the heat treatment.
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    ItemOpen Access
    Numerical aspects of a two-way coupling for electro-mechanical interactions - a wind energy perspective
    (2022) Lüdecke, Fiona Dominique; Schmid, Martin; Rehe, Eva; Panneer Selvam, Sangamithra; Parspour, Nejila; Cheng, Po Wen
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    ItemOpen Access
    Comparison of rotor arrangements of Transverse Flux Machines for a robotic direct drive optimized by genetic algorithm and Regression Tree Method
    (2023) Kaiser, Benedikt; Schmid, Martin; Parspour, Nejila
    Articulated robotics applications typically have a demand for high torque at low speed. However, conventional electrical machines cannot generate a reasonable amount of torque directly by electro-magnetics. Therefore, gearboxes are used to convert speed and torque, accepting loss of mechanical power due to additional friction. Although geared solutions for robotic drive trains already offer exceedingly high torque densities, they are limited by the drawbacks of high reduction gears, such as non-linearities in friction, complex flexibility effects, and limited service life of mechanics in contrary to direct drive solutions. The Transverse Flux Machine with the high gravimetric torque density may be a solution for reducing or eliminating the need for a gearbox. Using a genetic algorithm, the proposed Transverse Flux Machines are optimized. To enhance the optimization’s speed, the machines’ calculations done by Finite-Element-Analysis of selected generations are replaced by a Regression Tree Model whose results are verified after a defined expired model service life with a subsequent adjustment of the model. The eligibility of different arrangements the Transverse Flux Machines’ rotor are compared regarding the application as low-speed direct drive in robotics, also compared to similar Radial Flux Machines. The optimized Transverse Flux Machines have a higher efficiency due to lower copper loss and a higher active gravimetric torque density. However, the Radial Flux Machines have higher total torques and power factors.