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Paul Dicke, M.Sc.

Paul Dicke
  • Organization: Department of Computer Science
  • Working group: Chair of Computer Science 7 (Computer Networks and Communication Systems)
  • Phone number: +49 9131 85 27914
  • Fax number: +49 9131 85 27409
  • Email: paul.dicke@fau.de
  • Website:
  • Address:
    Martensstr. 3
    91058 Erlangen
    Room 06.157

Short Biography

Paul Dicke began to study Energy Technologies at FAU Erlangen-Nürnberg in 2011 and completed his studies 2016 with a Master’s degree specializing in energy process engineering. During this time, he worked several years for the Siemens AG in the field of brake architecture and software validation of high-speed trains. Since 2017 he works as a research assistant for the Chair of Computer Science 7 and started his doctoral studies within the framework of the project „Multi Battery Systems – Hybrid and New Storage Simulation Tool“, which addresses the modeling of electrochemical energy storage systems in the Software i7-AnyEnergy.

More Information

2019

2017

  • Multi Battery Systems - Hybrid and New Storage Simulation Tool

    (Third Party Funds Single)

    Term: 2017-05-01 - 2020-04-30
    Funding source: Siemens AG
    With the expansion of highly fluctuating renewables, the introduction of electric vehicles or securing the sufficient energy coverage of portable electronic devices electrochemical battery systems of each kind and dimensioning gain greater significance in various fields of everyday life. To assure cost- and time-efficient analysis for system design and project planning the usage of powerful models simulating the behavior of these battery systems is inevitable. In the project “Multi Battery Systems – Hybrid and New Storage Simulation Tool” in the context of FAU Campus – Future Energy Systems (FES) the Chair of Computer Science 7 (Computer Networks and Communication Systems) conceives detailed simulation models of several electrochemical battery storage systems. The project, which is realized in cooperation with Siemens AG Erlangen, aims to depict besides current storage technologies – like lithium-ion-batteries and lead-batteries – systems which thus far lack widespread application as well, like redox-flow-batteries or thermal batteries. In this manner, the designed models also extend the modular model-library of the software i7-AnyEnergy in order to enable more sophisticated analysis in distinct storage scenarios.