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In this paper the behavior of the three-way catalyst equipping a 2-liter car is fully analyzed considering exhaust gas and ceramic temperatures trends ( and of related engine parameters) in on-road operations of the car under different traffic conditions. These are classified by means of driving cycles clusters determined by multivariate statistical analysis of car speed and gear usage real profiles, detected on-road by the same car in designed experimental plans. Instantaneous fuel consumption and signals of a linear oxygen sensor, placed up-stream catalyst, have been analyzed to better characterize engine and catalyst performance. Emissions are measured in laboratory performing the most statistically representative driving cycles with car on the dynamometer chassis. The effect of traffic conditions on catalyst behavior and exhaust emissions is analyzed through the study of series of consecutive driving cycles.

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 statistical model for the evaluation of exhaust emissions of catalyst gasoline car operating under real conditions has been developed and proposed in this paper. Emission data, relative to tests performed in the laboratory simulating real driving conditions on the dynamometer chassis, are considered in the analysis. In the paper, the building and estimation of parameters of the statistical model developed according to the PLS approach is presented, as well as its application to the case of a small size gasoline catalyst car. Data and models of CO, HC, NOx and CO2 are compared with the results obtained by the application of the COPERT emission model to the specific car type.

The aim of this study is to develop an experimental approach and statistical methodology to assess the effectiveness of technological measures to improve vehicle emissions in real world use. The ultimate purpose is to provide a tool to support decisions made by public administrators and transit authorities, and assess the costs/benefits of environment-oriented investments. In this paper we report some results from the application of the proposed approach within a research project carried out by the Istituto Motori of the National Research Council of Italy, funded by the Ministry of the Environment, in cooperation with urban and extra-urban public transit companies and other public agencies. Our research focused on measuring particulate emissions in real use with and without an after-treatment device. Tests were performed in three Italian cities (Naples, Palermo and Lecce) using seven buses (homologation class EURO 0, 1 and 2) from three public local transit companies.

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.