Abstract:

The optimized battery power consumption law (also means the optimized control trajectory of the stage of charge (SOC) ) of plug-in hybrid electric vehicles (PHEVs) was obtained using a four-mode plug-in hybrid bus based on driving conditions. The main driving condition parameters that have the most influence on optimal SOC control trajectory were given by dynamic programming (DP) and correlation analysis method, and an optimized SOC trajectory planning method was proposed. The results of comprehensive driving cycles tests show that, compared with existing mileage-based linear programming method, the established SOC trajectory
planning method significantly reduced the SOC trajectory deviation from DP-based optimal results. The mean deviation was reduced by 75.2% to less than 3.6%, and the maximum deviation decreased by 72.3% to less than 8.2%. Computing time was reduced from 7.6~8.5 h to less than 0.18 s compared with DP. An adaptive
equivalent consumption minimization strategy (A-ECMS) that trace the planned SOC trajectory can improve the fuel economy, only 2.7% worse than DP, which can effectively solve the key problem of the on-line optimal planning of SOC trajectory and the energy optimal control, and provide a novel way for PHEV on-line energy
management optimization.

Key words: hybrid electric vehicle, plug-in hybrid electric vehicle (PHEV), energy management optimization, SOC trajectory planning, driving condition