A Study of Fuel Economy Improvement in a Plug-in Hybrid Electric Vehicle using Engine on/off and Battery Charging Power Control Based on Driver Characteristics

In this study, driving data for various types of drivers are collected using a VIDE (virtual integrated driving environment), and a driver model is developed. To represent the driver tendencies quantitatively, the DDA (degree of driver aggression) is proposed based on fuzzy logic. DDA has a 0-1 value; the closer the DDA is to one, the more aggressive the driver. Using the DDA, an engine on/off and battery charging power control algorithm are developed to improve the fuel economy of a power-split-type plug-in hybrid electric vehicle. The engine on/off control reduces the frequent engine on/off caused by aggressive driving, whereas the battery charging power control maintains the battery state of charge (SOC) by operating the engine according to the DDA. It is found that the proposed control algorithm improves fuel economy by 17.3% compared to the existing control for an aggressive driver.