Collaborative Energy Management for Intelligent Connected Plug-In Hybrid Electric Vehicles Based on Autonomous Speed Planning

This paper proposes a collaborative optimization strategy for speed planning and energy management of intelligent plug-in hybrid electric vehicles (PHEVs). In this study, a single-axis parallel PHEV with the powertrain of P2 configuration is employed as the research object. Then, dynamic programming (DP) is leveraged to ensure optimal fuel economy with the consideration of the simultaneous optimal demand torque distribution and autonomous speed selection. An adjustment coefficient that reasonably constrains the feasible domain of vehicle speed is designed to limit the range of autonomous speed selection according to driving conditions. The reasonableness of speed selection is enhanced by adding penalty functions to inhibit gear shifting and speed fluctuations. To consider the variability of the control strategies based on the constraints of travel time and distance, a time-domain and a space-domain collaborative optimization model are established respectively, and a simulation analysis of the collaborative optimization energy management strategy is conducted. The simulation result shows that the strategy achieves the collaborative optimization of speed autonomous planning and reasonable allocation for demand torque. In addition, the proposed strategy demonstrates preferable energy economy under different constraints based on time and space domains.