LAUSR

Dear editor, Ecological awareness and economical reasons call for a substantial reduction of the fuel consumption of all future automobiles. One of the most realistic short-term solutions to energy saving is represented by hybrid electric vehicles (HEVs). Those strategies that determine power distribution within the hybrid powertrain, as well as the gearshift schedule to enhance fuel economy are often referred as energy management systems (EMSs), such as rule-based methods [1,2] and optimizationbased methods [3–5]. In optimization-based methods, although numerous constraints exist, a truly optimal fuel consumption can be achieved when the entire driving cycle is known a priori. Another feasible approach to reduce energy consumption is “eco-driving”, which has gained wide attention from researchers because of its potential for using external information, such as those derived from navigation and intelligent transportation systems [4,6,7]. With the popularity of cruising system, the issue is to optimize vehicle speed and realize economic cruise, which plays a significant role in fuel economy. Therefore, for HEVs, the key of energy optimization is concentrated in cruise speed optimization and EMS [8]. In this study, we present a decomposition of the overall problem into two layers. The higher controller focuses on optimizing the velocity profile under the constraint of the preceding vehicle to minimize the overconsumption of energy with regard to the overall power output. The lower controller handles the optimization of torque split ratio and gearshift schedule, as shown in Figure 1(a). Different from other traditional EMS, the proposed method considers the influence of gearshift control and combines the velocity optimization and the powertrain control to improve fuel economy. System modeling and methodology. The dynamics of the vehicle longitudinal motion is