Research on the Driving Control Strategy for ISG Hybrid Electric Vehicles

ABSTRACT To overcome such Hybrid Electric Vehicle (HEV) engine problems as high fuel consumption and poor economical efficiency when working in low-efficiency areas, this paper intends to establish the ISG light hybrid vehicle structure-based mathematical models of engines, electric motors, batteries and the whole vehicle power output first; to analyse the relationship between the engine load rate and the optimal engine fuel consumption characteristics, and then to take into consideration the performance characteristics of the motor battery output efficiency, so as to come up with the switching pattern of the ISG parallel hybrid vehicle operating mode. According to the switching rules, the primary influence parameters of the engine load rate as well as the State of Charge (SOC) were extracted and a fuzzy neural network control strategy for torque management was developed. Under the Matlab/Advisor joint simulation platform, a simulation model was established and the effectiveness of the fuzzy control strategy was verified under the typical state of cyclic operation NEDC. The simulation results indicate that the adoption of fuzzy neural network control strategy for torque management can lead to considerable advancements in engine operating efficiency–the fuel economical efficiency can be improved by about 12%.