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

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/739140
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