Search Results

One of the objectives of the Atena project was the definition of methods for the predictive evaluation of the environmental impact of different types of vehicles used in an urban scenario. The target is to obtain a methodology that allows the decision maker to verify in simulation the effects of possible measures like the law enforcement to the access restrictions or vehicle fleet composition. The main obstacle is the realization and managing of real driving cycles in order to overtake the limits derived from the utilization of typical cycles (i.e., ECE + EUDC) or the simple consideration of average speed. The starting point is a digital representation of the urban network where all the roads are represented with one or more arcs and for all these arcs are available an estimation of the traffic variables like the vehicle flow (vehicles per hour) or the average speed (kph). Every arc is described in terms of traffic parameters like the type of road (i.e., highway, district road).

A novel model has been developed for the analysis and the evaluation of average vehicle emissions in a real driving cycle (emission factors) from data in an emission database. The model assumes that emission variation can be explained by parameters determined from dynamic vehicle equation and by the frequency of acceleration events at different speeds. Because the number of resulting X-variables is large, and variables are correlated, a regression method based on principal components, the Partial Least Squares (PLS) method actually, has been adopted. In this paper, model potentiality is illustrated by an application to a case study taken from the database built within the UE V Framework Project ARTEMIS. Data are relative to tests performed under hot conditions with a sample of EURO III 1.4-2.0 l gasoline passenger cars. A set of real driving cycles was utilized as representative of urban, rural and motorway operating conditions detected in different European countries.