Institute of Control Systems (IRS)

M. Sc. Oliver Stark

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

Curriculum Vitae

Qualification as electronics technician for automation technology with Volkswagen AG and IHK Braunschweig.

Studies of electrical engineering at Ostfalia University of Applied Science (Wolfenbüttel) in cooperation with Volkswagen AG. Bachelor’s thesis on the design and implementation of a time-discrete Hinf control for an electromechanical steering system (2014) with Steering Systems and Functional Development Unit of Volkswagen AG.

Then, studies of electrical engineering and information technology at Karlsruhe Institute of Technology, specialization in control technology. Master’s thesis at Institute of Control Systems on interval optimization-based identification methods (2016).

Since November 2016, member of scientific staff of Institute of Control Systems.


Online identification of physically interpretable system parameters of a lithium-ion battery

Energy transition is meeting with a steadily increasing interest of society. One of the central problems is energy storage, reasons being the large use of portable electronic devices, the electrification of private cars, and the better utilization of volatile energy sources.

Therefore, current research focuses on lithium-ion batteries, as these have a high energy density. But these kinds of batteries also have drawbacks, such as a low storage capacity. Moreover, many issues have not yet been solved, such as determination of the lithium-ion battery state. That is why various scientific groups are active in this area. Also at Institute of Control Systems, the lithium-ion battery is subject of research.

My doctoral thesis covers the development of an online identification method for interpreting the physical state of a lithium-ion battery. First, the battery model has to be derived from the mathematical description of chemical processes. Fractional models allow for such physical interpretation and their derivations no longer have to be integer. When deriving the model, it is also important to make simplifications as late as possible for the model parameters to keep their physical reference. The model parameters have to be identified online for physical state estimation. Then, the Institute of Control Systems developed identification method has to be developed for online operation based on modulation functions and to be assessed numerically.

The paramount objective is to optimize control of lithium-ion batteries by the battery management system based on knowledge of the parameter values in operation. This will ensure better utilization of resources.

Introduction in Fractional Analysis (german)