Title :
Study on genetic- fuzzy control strategy for PHEV drive system
Author :
Ma Xianghua ; Ye Yinzhong
Author_Institution :
Sch. of Electr. & Electron. Eng., Shanghai Inst. of Technol., Shanghai, China
Abstract :
To improve the fuel economy for driving system of parallel hybrid electric vehicles, in the paper the genetic algorithm is used to optimize the designed fuzzy controller. It has two input variables, which are the torque difference ΔT and the SOC of battery with one output variable the torque coefficient. The fuzzy control strategy before and after optimization is validated in the CYC CHINA cycle via ADVISOR2002. The simulation results show that the optimized fuzzy controller can further improve fuel economy and reduce the fluctuations of the final value of SOC.
Keywords :
control system synthesis; electric drives; fuel economy; fuzzy control; genetic algorithms; hybrid electric vehicles; secondary cells; ADVISOR2002; CYC CHINA cycle; PHEV drive system; battery SOC; driving system; fuel economy improvement; fuzzy controller design; genetic algorithm; genetic-fuzzy control strategy; input variables; optimization; parallel hybrid electric vehicles; torque difference; ADVISOR; Fuzzy logic control; PHEV; genetic algorithm; optimization;
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an
