Intelligent energy management of new energy vehicles is an important topic of advanced automotive technology research， and is critical to further improve the fuel economy performance of the entire vehicle. Aiming at the challenge of considering both real-time and optimal capabilities for global energy management and control of plug-in hybrid electric vehicle （PHEV）， this paper studies full trip adaptive energy management based on energy consumption prediction. An adaptive equivalent fuel consumption minimum control algorithm for full-trip PHEV is proposed. Finally， MATLAB/Simulink modeling and simulations are conducted， and the results show that the proposed control strategy has good followability and adaptability to the changes of actual driving conditions，driving mileage and automobiles’ energy states. The approximate global optimization control has good effects on the full path， and the fuel economy of the vehicle is significantly improved.