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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.

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.

Transport activities contribute significantly to the air pollution and its impact on emissions is a key element in the evaluation of any transport policy or plan. Calculation of emissions has therefore gained institutional importance in the European Community. To obtain emission factors several methods make use of only vehicle mean velocity, which can be easily obtained by vehicle flow and density in the road. Recently in ARTEMIS project by Rapone et al. (2005–2007) a meso scale emission model, named KEM (Kinematic Emission Model), able to calculate emission factor has been developed. This model is based on a new statistical methodology, capable to consider more attributes than the simple mean speed to characterize driving behaviour. An interesting approach to determine the exact mix of driving cycles is represented by the use of microscopic traffic simulation models that could be used to avoid the very expensive costs of experimental campaigns needed to obtain real driving cycle.

A system for both ignition and ion current measurement was designed and set up at Istituto Motori. Particular attention was paid to the problem of dissipating the residual energy stored in the ignition coil, reducing the electromagnetic interferences and especially improving the response of the measurement system. In order to assess the capability of the ion current signal to give reliable and accurate information for knock detection, a number of tests were carried out at full load on a commercial PFI four cylinder engine, at various air/fuel ratios and spark timings. Some knock indices based on the ionization signal, both band pass filtered and non-filtered, were introduced, in particular: the Amplitude of the Second Ionization Peak (ASIP), the Mean not filtered Ionization Current signal (MIC), the Maximum Amplitude of Ionization Current signal Oscillation (MAICO), the Integral of Modulus of filtered Ionization Current signal Oscillation (IMICO).

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.

Transport activities contribute significantly to air pollution. For this reason any policy or plan, carried out by administration or institution, requires the assessment of its impact on the emissions. To assess the overall pollutant production from transport, it is necessary to calculate emission factors. For this aim several methods exist which only use the average speed of the traffic stream, which can be theoretically obtained by vehicles flow and density on the road. Recently, a new statistical approach has been developed capable to consider more attributes than the simple mean speed to characterize driving behaviour, not only in the determination of driving cycles but also in the emission modelling. In this context, a meso scale emission model, named KEM, Kinematic Emission Model, able to calculate emission factor was developed. However, it is necessary to consider that the input to this model is, in any case, the driving cycle.

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.

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.