Assegnista di Ricerca
Dipartimento Energia (DENERG)
Docente esterno e/o collaboratore didattico
Dipartimento Energia (DENERG)
Dottorando in Energetica , 35o cycle (2019-2022)
Dipartimento Energia (DENERG)
Profilo
Dottorato di ricerca
Argomento di ricerca
Exploiting V2X connections and advanced energy management strategies to achieve maximum CO2 reductio
Tutori
Interessi di ricerca
Biografia
His Ph.D. is focused on hybrid electric vehicles to assess the CO2 emissions reduction that can be achieved by synergically exploiting V2X connections and advanced energy management strategies.
From November 1st, 2019 to August 31st, 2022, he was a visiting student researcher at Stanford University invited by Prof. Onori. His research activity, sponsored by Volkswagen Group of America (VWoA), was focused on the health estimation of battery packs combining electrochemical modelling and data-inspired algorithms.
Premi e riconoscimenti
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U.S. Patent Application: BATTERY MANAGEMENT SYSTEM FOR DETERMINING A HEALTH OF A POWER SOURCE BASED ON DRIVING EVENTS. For confidentiality reasons, only an extract has been uploaded. (2023) - U.S. Patent Application: BATTERY MANAGEMENT SYSTEM FOR DETERMINING A HEALTH OF A POWER SOURCE BASED ON AN IMPEDANCE INDICATOR. For confidentiality reasons, only an extract has been uploaded. (2023)
- U.S. Patent Application: BATTERY MANAGEMENT SYSTEM FOR DETERMINING A HEALTH OF A POWER SOURCE BASED ON CHARGING EVENTS.
For confidentiality reasons, only an extract has been uploaded. (2023)
- First Prize for the Student Awards at the FISITA World Conference 2021, with the paper entitled: “Energy Management System Optimization Based on V2X Connectivity”.
The Student Awards are awarded for the best 3 papers written and presented at Congress by an author under the age of 35. (2021)
Didattica
Insegnamenti
Corso di laurea magistrale
- Propulsori termici. A.A. 2022/23, INGEGNERIA MECCANICA. Collaboratore del corso
Ricerca
Gruppi di ricerca
Pubblicazioni
Pubblicazioni più recenti Vedi tutte le pubblicazioni su Porto@Iris
- Pulvirenti, L.; Rolando, L.; Millo, F. (2023)
Energy management system optimization based on an LSTM deep learning model using vehicle speed prediction. In: TRANSPORTATION ENGINEERING (OXFORD), vol. 11. ISSN 2666-691X
Contributo su Rivista - Millo, Federico; Rolando, Luciano; Tresca, Luigi; Pulvirenti, Luca (2023)
Development of a neural network-based energy management system for a plug-in hybrid electric vehicle. In: TRANSPORTATION ENGINEERING (OXFORD), vol. 11. ISSN 2666-691X
Contributo su Rivista - Millo, F; Rolando, L; Pulvirenti, L; Di Pierro, G (2022)
A Methodology for the Reverse Engineering of the Energy Management Strategy of a Plug -In Hybrid Electric Vehicle for Virtual Test Rig Development. In: SAE INTERNATIONAL JOURNAL OF ELECTRIFIED VEHICLES, vol. 11, pp. 113-132. ISSN 2691-3747
Contributo su Rivista - Millo, Federico; Rolando, Luciano; Pulvirenti, Luca (2021)
Energy Management System Optimization Based on V2X Connectivity. In: FISITA World Congress 2021, PRAGUE (CZ), 14–16 Settembre 2021. ISBN: 9781916025929
Contributo in Atti di Convegno (Proceeding)