Ph.D. in Energetica , 37th cycle (2021-2024)
Ph.D. obtained in 2025
Dissertation:
Advancing vehicle electrification: control strategies for hybrid electric vehicles and battery management algorithms for state estimation (Abstract)
Tutors:
Daniela Anna MisulPublications
Works published during the Ph.D. View all publications in Porto@Iris
- Acquarone, Matteo (2025)
Advancing vehicle electrification: control strategies for hybrid electric vehicles and battery management algorithms for state estimation. relatore: MISUL, DANIELA ANNA; , 37. XXXVII Ciclo, P.: 133
Doctoral Thesis - Acquarone, Matteo; Miretti, Federico; Giuliacci, Tiziano Alberto; Duque, Josimar; Misul, ... (2024)
Regression based battery state of health estimation for multiple electric vehicle fast charging protocols. In: JOURNAL OF POWER SOURCES, vol. 624. ISSN 0378-7753
Contributo su Rivista - Biswas, Atriya; Acquarone, Matteo; Wang, Hao; Miretti, Federico; Misul, Daniela Anna; ... (2024)
Safe Reinforcement Learning for Energy Management of Electrified Vehicle with Novel Physics-Informed Exploration Strategy. In: IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION. ISSN 2332-7782
Contributo su Rivista - Acquarone, Matteo; Miretti, Federico; Anselma, Pier Giuseppe; Misul, Daniela Anna (2024)
Online Temperature-aware Equivalent Consumption Minimization Strategy for Mild Hybrid Electric Powertrains. In: IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY. ISSN 0018-9545
Contributo su Rivista - Lanubile, Andrea; Bosoni, Pietro; Pozzato, Gabriele; Allam, Anirudh; Acquarone, Matteo; ... (2024)
Domain knowledge-guided machine learning framework for state of health estimation in Lithium-ion batteries. In: COMMUNICATIONS ENGINEERING, vol. 3. ISSN 2731-3395
Contributo su Rivista - Acquarone, Matteo; Miretti, Federico; Misul, Daniela; Sassara, Luca (2023)
Cooperative Adaptive Cruise Control Based on Reinforcement Learning for Heavy-Duty BEVs. In: IEEE ACCESS, vol. 11, pp. 127145-127156. ISSN 2169-3536
Contributo su Rivista - Acquarone, Matteo; Maino, Claudio; Misul, DANIELA ANNA; Spessa, Ezio; Mastropietro, ... (2023)
Influence of the Reward Function on the Selection of Reinforcement Learning Agents for Hybrid Electric Vehicles Real-Time Control. In: ENERGIES, vol. 16. ISSN 1996-1073
Contributo su Rivista - Borneo, Angelo; Miretti, Federico; Acquarone, Matteo; Misul, Daniela (2023)
Battery Electric Vehicle Control Strategy for String Stability based on Deep Reinforcement Learning in V2V Driving. In: 16th International Conference on Engines & Vehicles, Capri, Italy, September 10th - 14th, 2023, pp. 1-7. ISSN 0148-7191
Contributo in Atti di Convegno (Proceeding) - Acquarone, Matteo; Borneo, Angelo; Misul, Daniela Anna (2022)
Acceleration control strategy for Battery Electric Vehicle based on Deep Reinforcement Learning in V2V driving. In: 2022 IEEE Transportation Electrification Conference and Expo, ITEC 2022, Anaheim, CA, USA, 15-17 June 2022, pp. 202-207
Contributo in Atti di Convegno (Proceeding) - Acquarone, Matteo; Anselma, Pier Giuseppe; Miretti, Federico; Misul, Daniela (2022)
Battery temperature aware equivalent consumption minimization strategy for mild hybrid electric vehicle powertrains. In: 2022 IEEE Vehicle Power and Propulsion Conference (VPPC), Merced (USA), 01-04 November 2022, pp. 1-6. ISBN: 978-1-6654-7587-7
Contributo in Atti di Convegno (Proceeding)