Thesis - General comparison of ML methods for Li-Ion battery voltage prediction
AVL
- Graz, Steiermark
- Unbefristet
- Vollzeit
- Modeling of an electrical equivalent circuit of a battery (ECC)
- State Space Model (SS-Model) on time invariant model parameters (R & C constant)
- Implementation and comparison of different ML algorithms
- like NN, LSTM, Decision Trees, Gaussian Processes, Feature Engineering
- for system identification to predict the output voltage of a Li-Ion battery
- the ML algorithms are to be trained and validated on a synthetic data set generated by an ECC
- Comparison of at least two different ML algorithms (NN mandatory) to
- R & C parameter estimation
- Time variant model parameters (R & C) (optional)
- How can prior physical knowledge be used to improve the prediction (opt.)
- Good knowledge of English
- Programming skills in Python
- Knowledge of optimization methods and machine learning
- Electrical Engineering
- Computer Science/Data Science
- Digital Engineering