ANALYSIS OF THE THERMAL BEHAVIOR OF LITHIUM-ION CONTAINER BATTERY ENERGY STORAGE SYSTEMS (BESS) WITH REAL-WORLD DATA

Research Internship Topic

The Container format is currently the most preferred installation option for grid-connected Lithium-ion BESSs owing to enhanced safety, security, and performance. Li-ion batteries need to be operated within a certain temperature range for safe and optimal operation of the system, which results in lower cell degradation and better electrical performance. As these container BESSs are installed outdoors, and are exposed to the ambient temperature and the solar irradiation, Heating, Ventilation, Air Conditioning (HVAC) systems are necessary to ensure that the operating temperatures inside the containers stay within the stipulated range. A range of sensors installed in the systems log the temperature at various locations within the container in real-time to yield important insights relevant to the improvement of the design and layout of the HVAC system. The focus of this internship is on the acquisition and subsequent analysis of measured field-data from real-world systems.


The tasks for this research internship are

  1. Acquisition of measured field-data from real-world systems
  2. Pre-processing and preparation of data for analysis in python
  3. Parametrization of chosen real-world systems for simulation with SimSES, and comparison of simulation results with acquired field-data
  4. Detailed data analysis in python to highlight relations between the main influencing parameters, and discussion of the results.
  5. Acquisition of requisite data for tasks 1, 2, and 3 from various sources to aid the modelling procedure. This includes component datasheets and meteorological data for various locations

Who can apply

Students of master degree programs at TUM, specializing in energy/power/electrical/mechanical engineering with good knowledge of programming in python may apply. Depending on the program, a duration of 9 weeks (full-time) and 12 ECTS credits can typically be expected for this internship.


Starting date

Immediately


See also SimSES

time-series tool for detailed stationary storage system simulations


Send your applications to 

Anupam Parlikar anupam.parlikar@tum.de, Chair of Electrical Energy Storage Technology, TU München Felix Forster forster@smart-power.net, Smart Power GmbH, Munich, Germany

 

 

 

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