CREATOR Case: Induction Motor Data

In this repository, we are providing the machine design parameters and the experimental results of an induction motor (IM). This motor is one of the CREATOR [1] test case motors. As verification and validation of models has become increasingly important, so has the need for the availability of data...

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Hauptverfasser: Heidarikani, Kourosh, Dhakal, Pawan Kumar, Muetze, Annette, Seebacher, Roland
Format: Dataset
Sprache:eng
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Zusammenfassung:In this repository, we are providing the machine design parameters and the experimental results of an induction motor (IM). This motor is one of the CREATOR [1] test case motors. As verification and validation of models has become increasingly important, so has the need for the availability of data to allow for verification and validation of models, as well as the reproducibility and reusability of results. We developed the set of machine data for the multifaceted analysis. This allows the users to analyse both steady state and transient investigations as we are providing the measured low-frequency equivalent circuit parameters as well as comprehensive measurement results on six different drive cycles. This package of data provides all the required information in terms of design parameters and measurement results to facilitate their use as a validation and benchmarking tool for different modeling approaches, beyond the specific quantitative results as obtained from singular analyses. We thereby also contribute to increasing the availability of results in the field of electric machines that follow the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, which enables transparency and reproducibility of research knowledge. [1] The Computational Electric Machine Laboratory, Collaborative Research Centre CREATOR (CRC -- TRR361/F90) at TU Darmstadt, TU Graz, and JKU Linz is all about research and collaboration in various machine fields to enhance the machine design, analysis, and performance. With more than twenty research projects in four different areas of electromagnetics, fluid mechanics, numeric optimization, and also including the research data management, we try to address all the relevant aspects of a machine, e.g., shape and topology, time-dependent operating cycles, complex material behaviour, uncertainties and robustness, new cooling techniques to push thermal limits, noise and vibrations, and various key performance indicators.
DOI:10.3217/wjjn5-g2c09