Fuzzy control strategy of parallel HEV based on driving cycle recognition

Considering the effect of driving cycle to control strategy(CS), a fuzzy CS based on driving cycle recognition is presented in the paper to improve fuel economy of parallel hybrid electric vehicle(PHEV). The CS is composed of driving cycle recognition and fuzzy torque distribution controller. The present driving cycle is recognized by learning vector quantization combined with vehicle traveling parameters in driving cycle recognition. The torques of engine and motor are controlled by fuzzy torque distribution controller based on required torque of hybrid drive system and battery state of charge. The membership functions and rules of fuzzy torque distribution controller are optimized simultaneously by using particle swarm optimization. Based on the identification results of driving cycle recognition, fuzzy torque distribution controller selects corresponding membership function and rule to control hybrid system. The simulation research based on ADVISOR demonstrates that, compared with traditional fuzzy CS, the fuzzy CS based on driving cycle recognition improves fuel economy more effectively.