Wilhelm Kirchgässner

Leistungselektronik und Elektrische Antriebstechnik (LEA)
kirchgaessner@lea.uni-paderborn.de
ID
49265

15 Publications

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[15]
2024 | Dissertation | LibreCat-ID: 58756
Kirchgässner, Wilhelm. Data-Driven Thermal Modeling of a Permanent Magnet Synchronous Motor with Machine Learning. LibreCat University, 2024, doi:10.17619/UNIPB/1-2068.
LibreCat | DOI
 
[14]
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
 
[13]
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
 
[12]
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
 
[11]
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
 
[10]
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
 
[9]
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
 
[8]
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
 
[7]
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
 
[6]
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
 
[5]
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
 
[4]
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
 
[3]
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
 
[2]
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
 
[1]
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.
LibreCat | DOI
 
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15 Publications

Mark all

[15]
2024 | Dissertation | LibreCat-ID: 58756
Kirchgässner, Wilhelm. Data-Driven Thermal Modeling of a Permanent Magnet Synchronous Motor with Machine Learning. LibreCat University, 2024, doi:10.17619/UNIPB/1-2068.
LibreCat | DOI
 
[14]
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
 
[13]
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
 
[12]
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
 
[11]
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
 
[10]
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
 
[9]
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
 
[8]
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
 
[7]
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
 
[6]
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
 
[5]
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
 
[4]
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
 
[3]
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
 
[2]
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
 
[1]
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.
LibreCat | DOI
 
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Citation Style: MLA

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