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Background of thesis project
Fuel Cell technology is a promising solution to improve our current electromobility systems.
In fact, the usage of hydrogen as an energy vector can possibly increase the range and downsize the energy storage system.
Control and optimization of the whole system, propulsion as well as cooling system, becomes crucial to increase efficiency and meet the requirements.
Suitable background
Strong background in:
- Automatic control
- Dynamic modeling
- Optimization
- You should be able to use Matlab/Simulink and Python is a plus.
- It’s desirable to have notions about thermal engineering
Description of thesis work
Aim
The goal of the thesis is to design and implement a controller, possibly a Model Predictive Controller (MPC), that is able to increase the efficiency of a target system equipped with energy storage system, fuel cell, hydrogen storage and cooling system. Most of the simulation models are available and usable to support the control design.
First step
Literature study to benchmark the different solutions in terms of fuel cell vehicles (or systems in general) control leading to global optimization.
Second step
Linearize the models, identify an objective function and design the controller.
Third step
Verify the results and identify possible improvements.
Thesis Level: Master (30 ECTS points)
Language: English
Starting date: January 2023
Number of students: 1-2
Tutor
Francesco Galuppo, Senior CAE Engineer, Volvo Penta, +46765534247
Josef Backhans, CAE Simulation Manager, Volvo Penta, +46765534372