Control Strategy to Improve Fuel Economy for Plug-in Hybrid Electric Vehicle considering Degree of Driver Aggression

In this study, a control strategy to improve the fuel economy was proposed for a PHEV(plug-in hybrid electric vehicle) considering driver tendency. To identify the driver tendency, a driver model which reflects the driver tendency was developed using the driving data. The target PHEV model was developed based on MATLAB/Simulink and validation of the vehicle model was performed by experiments. From the driving data, the driver model which can reflect the driver tendency was developed. To describe the driver tendency, degree of driver aggression(DDA) was proposed, which was determined by fuzzy logic. Using the DDA, a PHEV control algorithm was proposed to improve the fuel economy, which consists of the engine on/off and battery charge-engine operation. The engine on/off control reduces frequent engine on/off for a high DDA(wild driver), whereas the battery charge-engine operation controls the engine operation by considering both the engine thermal efficiency and powertrain efficiency to maintain the battery SOC. It is expected that proposed control algorithm provides improved fuel economy of the target