His background
I studied at the University of Campania "Luigi Vanvitelli" for my BSc in Mechanical Engineering, and then at the University of Napoli "Federico II" for my MSc in Mechanical Engineering for Design and Manufacturing, focused on mechatronics systems. I had my first approach to the research field by developing my MSc thesis in collaboration with the Applied Mechanics research group of the University of Napoli, specialized in Vehicle Dynamics and Tyre Mechanics. In this context, I worked on several activities related to the understanding of the vibrations inherent the tire-road interaction, developing competences in both mathematical modelling of mechanics systems and indoor/outdoor experimental tyre/vehicle testing. Afterward, I also had the opportunity to work on a research project concerning autonomous driving systems for a private company in the automotive sector. These experiences made me aware of the enormous potential of scientific research and the special feelings that the daily challenges of such an activity can bring.
Key facts
- Step-by-step approach and positive attitude in facing new challenges.
- Desire to learn continuously, from and with people of different cultures and views.
- Interest in new technologies, motorsport, cinema.
Summary of his thesis
Worldwide governmental bodies and authorities are increasingly adopting comprehensive policies to promote the sustainability of the road transport sector, given its significant impact on energy demand, CO2 emissions, and air pollution. This is leading a transition from conventional Internal Combustion Engine (ICE) vehicles to cleaner and more efficient Electric Vehicles (EVs) that, however, are yet to provide a similar driving range offered by ICE systems. Therefore, to increase the potential travelled distance per charge, this research focuses on rolling resistance since it represents one of the main factors affecting a vehicle’s energy consumption. The main objective is to develop a data-driven prediction model to estimate rolling resistance for EVs along different types of road surfaces and in different driving conditions. To achieve this purpose, an instrumented EV will be used both on test tracks exhibiting a wide range of pavement mixtures and on real road sections. The sensory system will allow for measuring rolling resistance forces in the tyre/road contact area as well as vehicle dynamics and tyre operating conditions. Thus, data related to on-board vehicle measurements and the pavement surface characteristics will be used to train a machine learning model according to a multi-step approach. The latter will improve the EVs driving range estimation and the application of energy-saving algorithms.
What's next?
I'm going to work with dedication and enthusiasm to successfully develop this project and to fully experience the CLEAR-Doc program. Then, I'd like to pursue a career as a researcher-entrepreneur by applying the skills developed to start or contribute to entrepreneurial ventures, leveraging research and innovation.
However… you never know what's coming for you!
Gerardo GRAVANTE A machine learning-based rolling resistance prediction model for electric vehicles
