Data-driven thermal modeling of a permanent magnet synchronous motor with machine learning
W. Kirchgässner, Data-Driven Thermal Modeling of a Permanent Magnet Synchronous Motor with Machine Learning, LibreCat University, 2024.

Thermal neural networks: Lumped-parameter thermal modeling with state-space machine learning
W. Kirchgässner, O. Wallscheid, J. Böcker, Engineering Applications of Artificial Intelligence 117 (2022).

Learning Thermal Properties and Temperature Models of Electric Motors with Neural Ordinary Differential Equations
W. Kirchgässner, O. Wallscheid, J. Böcker, in: 2022 International Power Electronics Conference (IPEC-Himeji 2022- ECCE Asia), IEEE, 2022.

Application of Thermal Neural Networks on a Small-Scale Electric Motor
W. Kirchgässner, D. Wöckinger, O. Wallscheid, G. Bramerdorfer, J. Böcker, in: IKMT 2022; 13. GMM/ETG-Symposium, 2022, pp. 1–6.

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, W. Kirchgässner, O. Wallscheid, IEEE Open Journal of Power Electronics (2021) 187–201.

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 (2021) 2059–2067.

gym-electric-motor (GEM): A Python toolbox for the simulation of electric drive systems
P. Balakrishna, G. Book, W. Kirchgässner, M. Schenke, A. Traue, O. Wallscheid, Journal of Open Source Software (2021).

Thermal Neural Networks: Lumped-Parameter Thermal Modeling With State-Space Machine Learning
W. Kirchgässner, O. Wallscheid, J. Böcker, ArXiv Preprint ArXiv:2103.16323 (2021).

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 (2020) 1–10.

Estimating Electric Motor Temperatures with Deep Residual Machine Learning
W. Kirchgässner, O. Wallscheid, J. Böcker, IEEE Transactions on Power Electronics 36 (2020) 7480–7488.

Data-Driven Permanent Magnet Temperature Estimation in Synchronous Motors with Supervised Machine Learning
W. Kirchgässner, O. Wallscheid, J. Böcker, ArXiv Preprint ArXiv:2001.06246 (2020).

Controller Design for Electrical Drives by Deep Reinforcement Learning: A Proof of Concept
M. Schenke, W. Kirchgässner, O. Wallscheid, IEEE Transactions on Industrial Informatics (2019) 4650–4658.

Empirical Evaluation of Exponentially Weighted Moving Averages for Simple Linear Thermal Modeling of Permanent Magnet Synchronous Machines
W. Kirchgässner, O. Wallscheid, J. Böcker, in: 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), 2019.

Deep Residual Convolutional and Recurrent Neural Networks for Temperature Estimation in Permanent Magnet Synchronous Motors
W. Kirchgässner, O. Wallscheid, J. Böcker, in: 2019 IEEE International Electric Machines &; Drives Conference (IEMDC), 2019.

Investigation of long short-term memory networks to temperature prediction for permanent magnet synchronous motors
O. Wallscheid, W. Kirchgässner, J. Böcker, in: 2017 International Joint Conference on Neural Networks (IJCNN), 2017.