About the job
Join us in the development of control and assistance functions in the eBike sector through model-based methodologies. This internship offers a unique opportunity to create and parameterize a bicycle model using MATLAB/Python, tackling the complexities of parameter influences on functional development.
- After initial training, you will create a bike model and parameterize it using established methodologies (Meijaard, Papadopoulos, Ruina, Schwab, 2007). You will have access to measurements for model validation and a bicycle prototype.
- Next, you will adapt and implement intrusive Polynomial Chaos Expansion (PCE) within MATLAB/Python for the bicycle model.
- This will enable a systematic investigation of how model parameters affect system states.
- You will experimentally validate the results using the prototype.
- In the latter half of your internship, you will design a controller and test it through simulation, ensuring robust navigation of the bicycle along a pre-defined path under parameter uncertainties.
- Furthermore, you will identify the most critical parameters through a global sensitivity analysis and compile your findings into a comprehensive report.
