Modeling and control of an electric powertrain of fuel cell range extender buses using machine learning methods
- Type:Bachelorarbeit
- Date:ab 03 / 2023
- Tutor:
Modeling and control of an electric powertrain of fuel cell range extender buses using machine learning methods
Context
In order to make a positive contribution to reducing pollutant emissions in public transport, buses with alternative drives are increasingly being used. While purely battery-electric buses have a shorter range than conventional buses, fuel cell range extender technology (FC-REX) has emerged as a suitable alternative. By providing energy from the battery and the fuel cell, BZ-REX buses meet the requirements for the range needed in each case and represent an economical solution. In order to gain more information about BZ-REX vehicles, a simulation model is implemented to model essential energy flows, among other things.
To develop the simulation model, the electric powertrain is modeled to simulate the traction energy demand and the speed of the vehicle considering driving resistances.
Objectives
Within the scope of the bachelor thesis, the electric powertrain of a BZ-REX bus as well as its control is to be modeled physics- and data-based in Matlab/Simulink. Furthermore, the vehicle speed shall be simulated considering driving resistances. For the implementation of machine learning methods, data is required that can be independently simulated using suitable simulation software (e.g. CarMaker) can be generated synthetically.
Requirements
- Experience with Python, C++ orMatlab
- Basic knowledge of machine learning
- Independent and solution-oriented way of working