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This study aims to characterize real world bus driving behavior from data obtained in experimental campaigns using instrumented buses. An integrated statistical method to determine bus driving behavior, based on analysis of time series of bus speed and GPS location data, is illustrated in this paper. Kinematic features of bus operating conditions are characterized by multivariate analysis of trip speed time series. Each trip is analyzed within a multi-level hierarchical structure: sequence, sub-cycle, cycle (part of trip between two successive bus stops). Finally, a preliminary application of the proposed method is shown, based on data obtained with buses of different size and homologation class in Naples and Palermo. Reference driving cycles were built, for one line in both cities, taking the most statistically representative cycles of each line with regard to different traffic and road situations.

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.

Unregulated emissions of polycyclic aromatic hydrocarbons (PAHs), carbonylic compounds, benzene and particulate matter (PM) were quantified in exhausts of a vehicle fleet representative of in use gasoline cars. Emission factors were obtained during both cold and hot start driving cycles (from urban to motorway driving conditions). Carbonylic compounds were sampled by DNPH cartridges and analyzed by HPLC. Benzene and other light hydrocarbons were collected in bags and then analyzed by GC-FID. PAHs were trapped in XAD-2 cartridges and then analyzed by GC-MS. PM was sampled by using the gravimetric procedure required for diesel cars. The effect of technology is significant with respect to regulated and unregulated emissions but different emissive behavior was found by varying the driving cycles. Cold start has a major influence on hydrocarbon emissions (included unregulated ones). This experimental work was carried out within the framework of the EU Artemis project.

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.

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.

A 1.2 l instrumented car, equipped with an on-board acquisition system capable of detecting and recording car speed, gear, engine and catalyst operating parameters, has been tested in designed trips all over Naples urban area with different drivers. Driving cycles statistically representative of car operation under different traffic conditions in urban and expressway trips, have been determined by multivariate statistical analysis of speed and gear. Emission tests have been performed in the laboratory with car on the dynamometer chassis using defined driving cycles and engine/catalyst conditions to define emission factors for this type of car for a wide and significant spectrum of road performance.

The attention on emissions of two-wheelers has been poor in the past, but today in countries with a large two-wheeler population it gives a significant contribution to aggregate emissions. In this paper the results obtained on a fleet composed by 22 two-stroke motorcycles (including mopeds) are presented. Sixteen in-use mopeds and six 125 cm3 motorcycles have been tested over ECE 47 and ECE 40 driving cycles respectively. Regulated emissions (CO, HC, NOx), carbon dioxide, benzene and fuel consumption have been evaluated by fueling motorcycles with two different gasoline formulations. One gasoline was a commercial Italian leaded gasoline with 1% benzene content; the other was a lower benzene and aromatics content gasoline. Benzene emissions decreased according to benzene content of gasoline.

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.