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Thesis - Machine learning based testing of battery and fuel cells
Graz (Österreich)
Aktualität: 16.04.2024
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16.04.2024, AVL List GmbH
Graz (Österreich)
Thesis - Machine learning based testing of battery and fuel cells
Master Thesis
Fitting Physical Models to the test measurements of the Batteries or Fuel Cells are a powerful tool in capturing their inner characteristics. However, the fidelity of the physical model is highly dependent on the set of physical phenomena coved by mathematical formalism. Differently, testing based on data-driven models, like artificial neural networks (ANN) does not require the use of prior electrochemical knowledge and their inference relies entirely on the data collected during the testing. Although such data-driven models can be very accurate, they also require a large training dataset and do not generalize well outside the training data domain.
Development of machine learning methods
Implementation of the developed methods into AVL testing pipeline of Batteries and Fuel Cells
Overcoming limitations of sparse and out-of-distribution training datasets
Ongoing studies in the fields of Computer Science, Telematics, Physics or Electrical Engineering
Good programming skills in Python or C++
Knowledge of Machine Learning
Good knowledge of German and English
Skills in solving PDE are beneficial
For this thesis is your presence at our headquarter in Graz required!
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Thesis - Machine learning based testing of battery and fuel cells
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Graz (Österreich)