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14 Publications
2022 | Journal Article | LibreCat-ID: 34065
Kirchgässner, Wilhelm, et al. “Thermal Neural Networks: Lumped-Parameter Thermal Modeling with State-Space Machine Learning.” Engineering Applications of Artificial Intelligence, vol. 117, 105537, Elsevier BV, 2022, doi:10.1016/j.engappai.2022.105537.
LibreCat
| DOI
2022 | Conference Paper | LibreCat-ID: 32859
Kirchgässner, Wilhelm, et al. “Learning Thermal Properties and Temperature Models of Electric Motors with Neural Ordinary Differential Equations.” 2022 International Power Electronics Conference (IPEC-Himeji 2022- ECCE Asia), IEEE, 2022, doi:10.23919/ipec-himeji2022-ecce53331.2022.9807209.
LibreCat
| DOI
2022 | Conference Paper | LibreCat-ID: 42894
Kirchgässner, Wilhelm, et al. “Application of Thermal Neural Networks on a Small-Scale Electric Motor.” IKMT 2022; 13. GMM/ETG-Symposium, 2022, pp. 1–6.
LibreCat
2021 | Journal Article | LibreCat-ID: 22162
Book, Gerrit, et al. “Transferring Online Reinforcement Learning for Electric Motor Control From Simulation to Real-World Experiments.” IEEE Open Journal of Power Electronics, 2021, pp. 187–201, doi:10.1109/ojpel.2021.3065877.
LibreCat
| DOI
2021 | Journal Article | LibreCat-ID: 21251
Kirchgässner, Wilhelm, et al. “Data-Driven Permanent Magnet Temperature Estimation in Synchronous Motors with Supervised Machine Learning: A Benchmark.” IEEE Transactions on Energy Conversion, vol. 36, no. 3, 2021, pp. 2059–67, doi:10.1109/tec.2021.3052546.
LibreCat
| DOI
2021 | Journal Article | LibreCat-ID: 21254
Balakrishna, Praneeth, et al. “Gym-Electric-Motor (GEM): A Python Toolbox for the Simulation of Electric Drive Systems.” Journal of Open Source Software, 2498, 2021, doi:10.21105/joss.02498.
LibreCat
| DOI
2021 | Preprint | LibreCat-ID: 29655
Kirchgässner, Wilhelm, et al. “Thermal Neural Networks: Lumped-Parameter Thermal Modeling With State-Space Machine Learning.” ArXiv Preprint ArXiv:2103.16323, 2021.
LibreCat
2020 | Journal Article | LibreCat-ID: 21252
Traue, Arne, et al. “Toward a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor Control.” IEEE Transactions on Neural Networks and Learning Systems, 2020, pp. 1–10, doi:10.1109/tnnls.2020.3029573.
LibreCat
| DOI
2020 | Journal Article | LibreCat-ID: 21250
Kirchgässner, Wilhelm, et al. “Estimating Electric Motor Temperatures with Deep Residual Machine Learning.” IEEE Transactions on Power Electronics, vol. 36, no. 7, 2020, pp. 7480–88, doi:10.1109/tpel.2020.3045596.
LibreCat
| DOI
2020 | Journal Article | LibreCat-ID: 29640
Kirchgässner, Wilhelm, et al. “Data-Driven Permanent Magnet Temperature Estimation in Synchronous Motors with Supervised Machine Learning.” ArXiv Preprint ArXiv:2001.06246, 2020.
LibreCat
2019 | Journal Article | LibreCat-ID: 25030
Schenke, Maximilian, et al. “Controller Design for Electrical Drives by Deep Reinforcement Learning: A Proof of Concept.” IEEE Transactions on Industrial Informatics, 2019, pp. 4650–58, doi:10.1109/tii.2019.2948387.
LibreCat
| DOI
2019 | Conference Paper | LibreCat-ID: 21247
Kirchgässner, Wilhelm, et al. “Empirical Evaluation of Exponentially Weighted Moving Averages for Simple Linear Thermal Modeling of Permanent Magnet Synchronous Machines.” 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), 2019, doi:10.1109/isie.2019.8781195.
LibreCat
| DOI
2019 | Conference Paper | LibreCat-ID: 21249
Kirchgässner, Wilhelm, et al. “Deep Residual Convolutional and Recurrent Neural Networks for Temperature Estimation in Permanent Magnet Synchronous Motors.” 2019 IEEE International Electric Machines & Drives Conference (IEMDC), 2019, doi:10.1109/iemdc.2019.8785109.
LibreCat
| DOI
2017 | Conference Paper | LibreCat-ID: 21248
Wallscheid, Oliver, et al. “Investigation of Long Short-Term Memory Networks to Temperature Prediction for Permanent Magnet Synchronous Motors.” 2017 International Joint Conference on Neural Networks (IJCNN), 2017, doi:10.1109/ijcnn.2017.7966088.
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