Wilhelm Kirchgässner

Contact

Biography

Publications

Power Electronics and Electrical Drives

Research Associate - Machine Learning

VCard

Phone:

+49 5251 60-3011

Fax:

+49 5251 60-3443

E-mail:

kirchgaessner(at)lea.upb(dot)de

Office:

E4.133

Web:

Homepage

Visitor:

Pohlweg 55
33098 Paderborn

07/2018 - today	Wissenschaftlicher Mitarbeiter/ Doktorand Maschinelles Lernen im Kontext elektrischer Antriebstechnik und Leistungselektronik
08/2016 - 06/2018	Software-Ingenieur Continental Automotive GmbH, Babenhausen. Entwicklung eingebetteter Systeme, Koordination von Entwickler-Hubs, Toolchain, Lasten- und Pflichtenheft-Pflege.
10/2015 - 03/2016	Studentische Hilfskraft Uni Paderborn, PB (Fachbereich Nachrichtentechnik). Unit-Tests, Algorithmen-Konversion Matlab <-> Python.
04/2014 - 09/2015	Werkstudent Wincor Nixdorf, Paderborn. Systemtest, Integrationstest, Installationsroutinen.
07/2009 - 08/2013	Dual-Student Elektrotechnik, B.Sc. & Facharbeiter Elektroniker für Geräte u. Systeme Phoenix Contact Electronics GmbH, Bad Pyrmont. Hochschule Ostwestfalen-Lippe, Lemgo.

Open list in Research Information System

2021

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 (2021), pp. 1-1

DOI

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), pp. 187-201

DOI

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)

DOI

2020

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), pp. 1-10

DOI

Estimating Electric Motor Temperatures with Deep Residual Machine Learning

W. Kirchgässner, O. Wallscheid, J. Böcker, IEEE Transactions on Power Electronics (2020), 36(7), pp. 7480-7488

DOI

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

DOI

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), pp. 4650-4658

DOI

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

DOI

2017

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

DOI

Open list in Research Information System