@articleKirchgässner_Wallscheid_Böcker_2022, title=Thermal neural networks: Lumped-parameter thermal modeling with state-space machine learning, volume=117, DOI=10.1016/j.engappai.2022.105537, number=105537, journal=Engineering Applications of Artificial Intelligence, publisher=Elsevier BV, author=Kirchgässner, Wilhelm and Wallscheid, Oliver and Böcker, Joachim, year=2022 
LibreCat: /record/34065
DOI: 10.1016/j.engappai.2022.105537

@inproceedingsKirchgässner_Wallscheid_Böcker_2022, title=Learning Thermal Properties and Temperature Models of Electric Motors with Neural Ordinary Differential Equations, DOI=10.23919/ipec-himeji2022-ecce53331.2022.9807209, booktitle=2022 International Power Electronics Conference (IPEC-Himeji 2022- ECCE Asia), publisher=IEEE, author=Kirchgässner, Wilhelm and Wallscheid, Oliver and Böcker, Joachim, year=2022 
LibreCat: /record/32859
DOI: 10.23919/ipec-himeji2022-ecce53331.2022.9807209

@inproceedingsKirchgässner_Wöckinger_Wallscheid_Bramerdorfer_Böcker_2022, title=Application of Thermal Neural Networks on a Small-Scale Electric Motor, booktitle=IKMT 2022; 13. GMM/ETG-Symposium, author=Kirchgässner, Wilhelm and Wöckinger, Daniel and Wallscheid, Oliver and Bramerdorfer, Gerd and Böcker, Joachim, year=2022, pages=1–6 
LibreCat: /record/42894

@articleBook_Traue_Balakrishna_Brosch_Schenke_Hanke_Kirchgässner_Wallscheid_2021, title=Transferring Online Reinforcement Learning for Electric Motor Control From Simulation to Real-World Experiments, DOI=10.1109/ojpel.2021.3065877, journal=IEEE Open Journal of Power Electronics, author=Book, Gerrit and Traue, Arne and Balakrishna, Praneeth and Brosch, Anian and Schenke, Maximilian and Hanke, Sören and Kirchgässner, Wilhelm and Wallscheid, Oliver, year=2021, pages=187–201 
LibreCat: /record/22162
DOI: 10.1109/ojpel.2021.3065877

@articleKirchgässner_Wallscheid_Böcker_2021, title=Data-Driven Permanent Magnet Temperature Estimation in Synchronous Motors with Supervised Machine Learning: A Benchmark, volume=36, DOI=10.1109/tec.2021.3052546, number=3, journal=IEEE Transactions on Energy Conversion, author=Kirchgässner, Wilhelm and Wallscheid, Oliver and Böcker, Joachim, year=2021, pages=2059–2067 
LibreCat: /record/21251
DOI: 10.1109/tec.2021.3052546

@articleBalakrishna_Book_Kirchgässner_Schenke_Traue_Wallscheid_2021, title=gym-electric-motor (GEM): A Python toolbox for the simulation of electric drive systems, DOI=10.21105/joss.02498, number=2498, journal=Journal of Open Source Software, author=Balakrishna, Praneeth and Book, Gerrit and Kirchgässner, Wilhelm and Schenke, Maximilian and Traue, Arne and Wallscheid, Oliver, year=2021 
LibreCat: /record/21254
DOI: 10.21105/joss.02498

@articleKirchgässner_Wallscheid_Böcker_2021, title=Thermal Neural Networks: Lumped-Parameter Thermal Modeling With State-Space Machine Learning, journal=arXiv preprint arXiv:2103.16323, author=Kirchgässner, Wilhelm and Wallscheid, Oliver and Böcker, Joachim, year=2021 
LibreCat: /record/29655

@articleTraue_Book_Kirchgässner_Wallscheid_2020, title=Toward a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor Control, DOI=10.1109/tnnls.2020.3029573, journal=IEEE Transactions on Neural Networks and Learning Systems, author=Traue, Arne and Book, Gerrit and Kirchgässner, Wilhelm and Wallscheid, Oliver, year=2020, pages=1–10 
LibreCat: /record/21252
DOI: 10.1109/tnnls.2020.3029573

@articleKirchgässner_Wallscheid_Böcker_2020, title=Estimating Electric Motor Temperatures with Deep Residual Machine Learning, volume=36, DOI=10.1109/tpel.2020.3045596, number=7, journal=IEEE Transactions on Power Electronics, author=Kirchgässner, Wilhelm and Wallscheid, Oliver and Böcker, Joachim, year=2020, pages=7480–7488 
LibreCat: /record/21250
DOI: 10.1109/tpel.2020.3045596

@articleKirchgässner_Wallscheid_Böcker_2020, title=Data-Driven Permanent Magnet Temperature Estimation in Synchronous Motors with Supervised Machine Learning, journal=arXiv preprint arXiv:2001.06246, author=Kirchgässner, Wilhelm and Wallscheid, Oliver and Böcker, Joachim, year=2020 
LibreCat: /record/29640

@articleSchenke_Kirchgässner_Wallscheid_2019, title=Controller Design for Electrical Drives by Deep Reinforcement Learning: A Proof of Concept, DOI=10.1109/tii.2019.2948387, journal=IEEE Transactions on Industrial Informatics, author=Schenke, Maximilian and Kirchgässner, Wilhelm and Wallscheid, Oliver, year=2019, pages=4650–4658 
LibreCat: /record/25030
DOI: 10.1109/tii.2019.2948387

@inproceedingsKirchgässner_Wallscheid_Böcker_2019, title=Empirical Evaluation of Exponentially Weighted Moving Averages for Simple Linear Thermal Modeling of Permanent Magnet Synchronous Machines, DOI=10.1109/isie.2019.8781195, booktitle=2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), author=Kirchgässner, Wilhelm and Wallscheid, Oliver and Böcker, Joachim, year=2019 
LibreCat: /record/21247
DOI: 10.1109/isie.2019.8781195

@inproceedingsKirchgässner_Wallscheid_Böcker_2019, title=Deep Residual Convolutional and Recurrent Neural Networks for Temperature Estimation in Permanent Magnet Synchronous Motors, DOI=10.1109/iemdc.2019.8785109, booktitle=2019 IEEE International Electric Machines &; Drives Conference (IEMDC), author=Kirchgässner, Wilhelm and Wallscheid, Oliver and Böcker, Joachim, year=2019 
LibreCat: /record/21249
DOI: 10.1109/iemdc.2019.8785109

@inproceedingsWallscheid_Kirchgässner_Böcker_2017, title=Investigation of long short-term memory networks to temperature prediction for permanent magnet synchronous motors, DOI=10.1109/ijcnn.2017.7966088, booktitle=2017 International Joint Conference on Neural Networks (IJCNN), author=Wallscheid, Oliver and Kirchgässner, Wilhelm and Böcker, Joachim, year=2017 
LibreCat: /record/21248
DOI: 10.1109/ijcnn.2017.7966088