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Wilhelm Kirchgässner
Wilhelm Kirchgässner
Verified email at lea.upb.de - Homepage
Title
Cited by
Cited by
Year
Estimating electric motor temperatures with deep residual machine learning
W Kirchgässner, O Wallscheid, J Böcker
IEEE Transactions on Power Electronics 36 (7), 7480-7488, 2020
992020
Data-driven permanent magnet temperature estimation in synchronous motors with supervised machine learning: A benchmark
W Kirchgässner, O Wallscheid, J Böcker
IEEE Transactions on Energy Conversion 36 (3), 2059-2067, 2021
652021
Deep residual convolutional and recurrent neural networks for temperature estimation in permanent magnet synchronous motors
W Kirchgässner, O Wallscheid, J Böcker
2019 IEEE International Electric Machines & Drives Conference (IEMDC), 1439-1446, 2019
612019
Controller design for electrical drives by deep reinforcement learning: A proof of concept
M Schenke, W Kirchgässner, O Wallscheid
IEEE Transactions on Industrial Informatics 16 (7), 4650-4658, 2019
572019
Investigation of long short-term memory networks to temperature prediction for permanent magnet synchronous motors
O Wallscheid, W Kirchgässner, J Böcker
2017 International joint conference on neural networks (IJCNN), 1940-1947, 2017
512017
Toward a reinforcement learning environment toolbox for intelligent electric motor control
A Traue, G Book, W Kirchgässner, O Wallscheid
IEEE Transactions on neural networks and learning systems 33 (3), 919-928, 2020
472020
Empirical evaluation of exponentially weighted moving averages for simple linear thermal modeling of permanent magnet synchronous machines
W Kirchgässner, O Wallscheid, J Böcker
2019 IEEE 28th International Symposium on industrial electronics (ISIE), 318-323, 2019
372019
Transferring online reinforcement learning for electric motor control from simulation to real-world experiments
G Book, A Traue, P Balakrishna, A Brosch, M Schenke, S Hanke, ...
IEEE Open Journal of Power Electronics 2, 187-201, 2021
322021
Thermal neural networks: Lumped-parameter thermal modeling with state-space machine learning
W Kirchgässner, O Wallscheid, J Böcker
Engineering Applications of Artificial Intelligence 117, 105537, 2023
232023
Gym-electric-motor (GEM): A python toolbox for the simulation of electric drive systems
P Balakrishna, G Book, W Kirchgässner, M Schenke, A Traue, ...
Journal of Open Source Software 6 (58), 2498, 2021
182021
Learning thermal properties and temperature models of electric motors with neural ordinary differential equations
W Kirchgässner, O Wallscheid, J Böcker
2022 International Power Electronics Conference (IPEC-Himeji 2022-ECCE Asia …, 2022
52022
Reinforcement learning course material
W Kirchgässner, M Schenke, O Wallscheid, D Weber
Paderborn Univ., Paderborn, Germany, 2020
42020
HARDCORE: H-field and power loss estimation for arbitrary waveforms with residual, dilated convolutional neural networks in ferrite cores
N Förster, W Kirchgässner, T Piepenbrock, O Schweins, O Wallscheid
arXiv preprint arXiv:2401.11488, 2024
2024
Application of Thermal Neural Networks on a Small-Scale Electric Motor
W Kirchgaessner, D Woeckinger, O Wallscheid, G Bramerdorfer, ...
IKMT 2022; 13. GMM/ETG-Symposium, 1-6, 2022
2022
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