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M. Sc. Christoph Schnurr

Research Associate

Guarantees by Design

Office Hours: 

Mittwoch 14:30-16:00 (nach Absprache)

Room: Geb. 30.33 (ITE) Raum 109
Phone: +49 721 608 - 45469
Fax: +49 721 608 - 42707
christoph schnurrKji4∂kit edu

Karlsruher Institut für Technologie (KIT)
Campus Süd
Institut für Regelungs- und Steuerungssysteme
Geb. 11.20 (Engler-Villa)
Kaiserstr. 12
D-76131 Karlsruhe

Curriculum Vitae

Studies of mechatronics at the Karlsruhe Cooperative State University (B.Eng. 2010).

Practical work and bachelor’s thesis with Schneider Electric Automation GmbH in Lahr/Schwarzwald.

Studies of electrical engineering and information technology, with a specialization in drives and power electronics, at Karlsruhe Institute of Technology and the Norwegian University of Science and Technology (M.Sc. 2013).

Master’s thesis at the Institute of Control Systems (IRS) of KIT on the design of an interval observer for asynchronous machines based on a hybridization approach. Since June 2014, member of the scientific staff of IRS.


Suitable energy storage systems for electric mobility are still lacking, as a result of which research to increase the efficiency of the drive train was intensified in the past years. Apart from optimizing the electric machine and power electronics, further development of the control concepts used is reasonable. The control strategy for traction drives is based on cascade control of the electric motor and separate control of power electronics.

Model Predictive Control (MPC) has long been used successfully in processing industry, but hardly is of importance for the control of drives outside of research. The main reason is the high calculation effort associated with this type of control. However, this is no obstacle for processes with large time constants. Major further developments of algorithms and processors make these approaches attractive for far highly dynamic systems.

Use of MPC for drives is motivated by the fact that several control objectives are pursued, such that online losses are minimized and best dynamics are achieved. A systematic approach using precise (loss) models of the components promises to reduce the parameterization expenditure for different machines compared to the state of the art. Another advantage is flexible consideration and full use of operation limits.

The research project is aimed at adapting and optimizing MPC for electrical drives. Implementation of the concept developed and investigation of the resulting potentials are to result in advantages compared to conventional control of traction drives.


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