This paper proposes a distributed Nonlinear Model Predictive Control (NMPC) strategy for a fleet of connected Hybrid Electric Vehicles that move in a coordinated fashion, optimizing fuel economy and battery state of charge. The numerical validation is provided by considering a commuter cycle usually exploited during real on-the-road emission tests. Results, carried out by exploiting ADVISOR- a state of the art simulation environment for modeling and control of hybrid electric vehicles- confirm the effectiveness of the approach.
Optimization of fuel consumption and battery life cycle in a fleet of Connected Hybrid Electric Vehicles via Distributed Nonlinear Model Predictive Control / Amodeo, Marco; Vaio, Marco Di; Petrillo, Alberto; Salvi, Alessandro; Santini, Stefania. - (2018), pp. 947-952. (Intervento presentato al convegno 16th European Control Conference, ECC 2018 tenutosi a cyp nel 2018) [10.23919/ECC.2018.8550511].
Optimization of fuel consumption and battery life cycle in a fleet of Connected Hybrid Electric Vehicles via Distributed Nonlinear Model Predictive Control
Petrillo, Alberto;Santini, Stefania
2018
Abstract
This paper proposes a distributed Nonlinear Model Predictive Control (NMPC) strategy for a fleet of connected Hybrid Electric Vehicles that move in a coordinated fashion, optimizing fuel economy and battery state of charge. The numerical validation is provided by considering a commuter cycle usually exploited during real on-the-road emission tests. Results, carried out by exploiting ADVISOR- a state of the art simulation environment for modeling and control of hybrid electric vehicles- confirm the effectiveness of the approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
