| KEYWORD |
Area Engineering
Development of a light-duty hybrid vehicle model in GT-SUITE environment
Reference persons STEFANO D'AMBROSIO
Research Groups PT-ERC
Description FRAMEWORK
Significant research efforts in reducing CO 2 and pollutant emissions from the transport sector are currently ongoing. To this aim, several technologies are under investigation, among which the electrification of the powertrain will surely play a significant role in the next decades. However, considering that fully electric vehicles are still facing limitations in terms of driving range, costs, needed infrastructure and safety, hybrid electric vehicles (HEVs), which include an internal combustion engine (ICE) and one or more electric machines, are expected to play a significant role in the near future. This is particularly true for light-duty and heavy-duty applications, for which diesel engines remain the most competitive solution. Therefore, research efforts in improving their environmental impact are still ongoing.
The present thesis work will be carried out within this framework, and will be focused on the development of a dynamic model of a light-duty hybrid vehicle in GT-SUITE environment.
THESIS DESCRIPTION
Task 1. Literature research concerning the state of the art in dynamic modeling of light-duty hybrid vehicles.
Task 2. Development of a dynamic model of a light-duty vehicle in GT-suite environments, starting from an already developed model of a conventional light-duty vehicle.
Task 3: Assessment of the model and integration of a simple-rule-based strategy for the energy flow optimization
See also proposta di tesi di laurea - vehicle modeling.docx
Required skills - Basic knowledge of GT-SUITE environment, but not mandatory. Specific tutorials will be carried out at the beginning of the activity.
- Basic knowledge on hybrid powertrains
Notes Expected learning outcomes
The student will acquire high level skills on the use of GT-SUITE software, as well as on hybrid powertrain / vehicle modeling.
Available material
GT-SUITE tutorials, bibliography
Notes
The activity will be supervised also by PhD students
Deadline 25/10/2025
PROPONI LA TUA CANDIDATURA