ACQUARONE, MATTEO

ACQUARONE, MATTEO  

Dipartimento Energia  

091237  

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Citazione Data di pubblicazione Autori File
Acceleration control strategy for Battery Electric Vehicle based on Deep Reinforcement Learning in V2V driving / Acquarone, Matteo; Borneo, Angelo; Misul, Daniela Anna. - ELETTRONICO. - (2022), pp. 202-207. (Intervento presentato al convegno 2022 IEEE Transportation Electrification Conference and Expo, ITEC 2022 tenutosi a Anaheim, CA, USA nel 15-17 June 2022) [10.1109/ITEC53557.2022.9813785]. 1-gen-2022 Acquarone, MatteoBorneo, AngeloMisul, Daniela Anna Acceleration_control_strategy_for_Battery_Electric_Vehicle_based_on_Deep_Reinforcement_Learning_in_V2V_driving.pdfAcceleration_control_strategy_for_Battery_Electric_Vehicle_based_on_Deep_Reinforcement_Learning_in_V2V_driving_.pdf
Battery temperature aware equivalent consumption minimization strategy for mild hybrid electric vehicle powertrains / Acquarone, Matteo; Anselma, Pier Giuseppe; Miretti, Federico; Misul, Daniela. - ELETTRONICO. - (2022), pp. 1-6. (Intervento presentato al convegno 2022 IEEE Vehicle Power and Propulsion Conference (VPPC) tenutosi a Merced (USA) nel 01-04 November 2022) [10.1109/VPPC55846.2022.10003225]. 1-gen-2022 Acquarone, MatteoAnselma, Pier GiuseppeMiretti, FedericoMisul, Daniela Battery_temperature_aware_equivalent_consumption_minimization_strategy_for_mild_hybrid_electric_vehicle_powertrains.pdf2022001830.pdf
Influence of the Reward Function on the Selection of Reinforcement Learning Agents for Hybrid Electric Vehicles Real-Time Control / Acquarone, Matteo; Maino, Claudio; Misul, DANIELA ANNA; Spessa, Ezio; Mastropietro, Antonio; Sorrentino, Luca; Busto, Enrico. - In: ENERGIES. - ISSN 1996-1073. - ELETTRONICO. - 16:6(2023), p. 2749. [10.3390/en16062749] 1-gen-2023 Matteo AcquaroneClaudio MainoDaniela MisulEzio SpessaAntonio MastropietroLuca Sorrentino + Influence of the Reward Function on the Selection of.pdf