This paper presents an ecological (eco) driving system based on prediction of the preceding vehicle using model predictive control. At any measured road-traffic states it computes the optimal vehicle control input using the models of the vehicle dynamics and fuel consumption. The prediction model the preceding vehicle is formulated based on experimentally obtained driving data. The proposed sys...

The thermodynamic cycle of an intercooled turbofan engine was optimized by considering various characteristics of intercoolers (ICs). Sixty-three intercooled turbofan engines were optimized using an evolutionary algorithm. Thirty-nine design parameters were analyzed using proper orthogonal decomposition, and the effects of the IC performance on the engine thermodynamic cycle were examined. The ...

Many companies are investing in coaching services for professional drivers with the goal of teaching them how to reduce fuel usage, as well as other eco-driving skills. To succeed, a clear perception of the variations in fuel consumption that can be attributed to driving behaviour is required. Currently, vehicles operated by CGI client Scania Group, a leading global transport provider, are equi...

While it is well known that “MPG will vary” based on how one drives, little independent research exists on the aggregate fuel savings potential of improving driver efficiency and on the best ways to motivate driver behavior changes. This paper finds that reasonable driving style changes could deliver significant national petroleum savings, but that current feedback approaches may be insufficien...

This paper presents real time fuzzy logic controller (FLC) approach used to design a power management strategy for a hybrid electric vehicle and to protect the battery from overcharging during the repetitive braking energy accumulation. The fuel cell (FC) and battery (B)/supercapacitor (SC) are the primary and secondary power sources, respectively. This paper analyzes and evaluates the performa...

Previously, researchers who developed representative driving cycles mainly focused on light-duty vehicles and only considered vehicle speed related derivations. In this paper, we propose a novel approach to develop for heavy-duty vehicles. By implementing decision tree regression (DTR) the Fleet DNA on-road data, broader set of metrics, such as engine power fuel consumption, can be used more ro...

Abstract Due to the technological progress, new approaches such as model-based design are spreading in development process automotive industry meet increased requirements related lower fuel consumption and reduced emission. This work is part of a research project which focuses on dynamic modeling vehicles aimed at analyzing optimizing emission consumption. To model driver behavior, simulation c...