Intelligent fuzzy energy management research for a uniaxial parallel hybrid electric vehicle

Abstract

In this paper, an intelligent fuzzy logic control strategy optimized by genetic algorithm (GA) has been proposed for uniaxial parallel hybrid electric vehicle (PHEV), in the fuzzy controller, the ratio between the motor target torque and the total demand torque is the first input variable, and the state of charge (SOC) of the battery is the second input variable. The torque distribution coefficient between the engine and the motor is as the output variable. The proposed strategy is compared to the electric auxiliary control strategy. The whole vehicle is modeled based on experimental data and the strategy is verified in automotive simulation software ADVISOR, the results show that the proposed control strategy can reduce fuel consumption, reduce emissions, ensure balanced charging and discharging of the battery, effectively avoid the production of the engine peak torque, and improve the overall performance of the vehicle.