Abstract: An energy management strategy for hybrid electric vehicles (HEV) was constructed and simulated according to the adaptive equivalent fuel consumption minimization strategy (A-ECMS) based on driving intention cloud model recognition. The cloud model algorithm was used to identify driving intentions to obtain the intention recognition results under some typical driving conditions. By using a weighted average method to establish the look-up table of equivalent factor to calculate the corresponding equivalent factors under each intention. The results show that the proposed A-ECMS strategy improves fuel economy by 1.3% compared with the A-ECMS based on SOC (state of charge) feedback under the New European Drive Cycle (NEDC). By using ECMS strategy obtains a similar fuel economy under combination condition with a better SOC stability. Therefore, the proposed A-ECMS strategy improves the practical application of the old ECMS strategy with a good reflecting for different driving intentions. 

Key words: hybrid electric vehicles (HEV), energy management, equivalent consumption minimization strategy (ECMS), adaptive-ECMS (A-ECMS), energy management, driving intentions, cloud model, simulation