Integrated Powertrain Energy Management and Vehicle Coordination for Multiple Connected Hybrid Electric Vehicles

This paper investigates the integrated optimization of internal powertrain energy management and external vehicles coordination for multiple autonomous and connected hybrid electric vehicles (HEVs). Most existing research on hybrid vehicles powertrain energy management only considers a single vehicle scenario and is independent from vehicle coordination control. With the advancement of connected and autonomous vehicles, optimizing both the vehicle level coordination and powertrain level power management together can bring in substantial benefits in the overall energy efficiency. In this paper, to enable such an integrated optimization scheme, first, the models of the external vehicle level dynamics and internal powertrain dynamics are built for each vehicle. Second, by integrating the dynamics of these two interactive levels together, an augmented system is formed. Then, the HEVs energy management problem and the decentralized vehicle coordination for a set of HEVs are addressed in a unified framework using dynamic programming. The results show that, as a result of the integrated optimization, the vehicles are able to operate close to the most fuel-efficient region, and the battery can avoid being depleted or over charged while maintaining the same state of charge at the beginning and the end. Moreover, much less fuel consumption can be achieved for the driving cycle considered, compared with the separated optimization method.