Optimization Of Fuel Consumption And Battery Life Cycle In A Fleet Of Connected Hybrid Electric Vehicles Via Distributed Nonlinear Model Predictive Control

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.