Development of a control algorithm to improve fuel economy for PREY considering driver tendency

Abstract

In this study, an engine on/off and engine operation control algorithm to improve the fuel economy was proposed for a PREV(plug-in hybrid electric vehicle) considering driver tendency. To identify the driver tendency, a driver model was developed using VIDE(virtual integrated development environment). The target vehicle model was developed based on MATLAB/Simulink and validation of the vehicle model was performed by experiments. Using the VIDE, real drivers who have different tendency drive the PHEV in virtual environment and driving data were accumulated. Using 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. The DDA was applied to the PREY control algorithm to improve the fuel economy. This algorithm controls the engine on/off and engine operation, which provides the improved fuel economy. © 2015 European Union.