Master Thesis: Development and Validation of an Efficient Simulation Model for Force-Induced Tyre Deformations

You will work on developing and validating an efficient simulation model to determine force-induced tyre deformations.

The dynamic wheel space requirement of sports vehicles is significantly influenced by the force-induced deformation of the tyre, which reaches its maximum in the vehicle's dynamic limit range.

Your tasks will include:

• Conducting literature research on existing tyre simulation models and surrogate modelling methods
• Investigating and evaluating relevant input and output variables for predicting geometric tyre deformation
• Generating a data basis for deformation characteristics in the limit range using RMOD-K simulations
• Developing, training, and validating an efficient surrogate model to represent the deformation of a reference tyre
• Extending the model to a parametric surrogate model by integrating selected structural parameters from MF-Swift datasets
• Evaluating the model's generalisation ability regarding its transferability to tyres from different manufacturers and dimensions
• Integrating the method into the existing process and documenting the results

Requirements:

• Currently pursuing a Master's degree in Vehicle Engineering, Computer Science, Data Science, Mechanical Engineering, or a related field
• Strong knowledge of vehicle dynamics, numerical simulation, and data analysis
• Proficiency in Python, MATLAB/Simulink, and data analysis/machine learning libraries
• Experience with LaTeX is a plus
• Excellent communication and teamwork skills
• Fluent in English and German