Energy Management Strategy Optimization of HEV based on Driving Pattern Recognition - Liu Yonggang; Xie Qingbo; Qin Datong; Lei Zhenzhen (Jixie chuandong)
The existing energy management strategy which is based on driving pattern recognition failed to fully consider the battery state of charge（ SOC） falling fast in some driving cycle into consideration in the progress of driving. The 23 typical driving cycles are chosen from ADVISOR software and five categories are divided by using clustering analysis method,the key parameters of each category are optimized by using particle swarm algorithm,with the goal of reducing fuel consumption,relevant optimized results are saved in database,an energy management strategy optimization method of HEV based on driving pattern recognition is proposed.Finally,the simulation analysis for the energy management is carried out under a comprehensive test cycle,simulation results show that vehicle fuel consumption is cut down 12. 77%,and the deviation of the battery SOC have greatly decrease compare with other energy management strategy which based on driving pattern recognition.