Emission Factors Determination of Euro III 1,200- to 1,400-cc Petrol Passenger Cars with a PLS Multivariate Regression Model

Rapone, M.; Prati, Maria Vittoria; Costagliola, Maria Antonietta; Ragione, L. Della; Meccariello, Giovanni

doi:10.1007/s10666-007-9108-4

Cited by 18 publications

(8 citation statements)

References 6 publications

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“…CMEM (Scora and Barth, 2006). Detailed information on vehicle state and emission is therefore required to determine model forms and to estimate model parameters (Rapone et al, 2008). …”

Section: Emission Estimation Modelsmentioning

confidence: 99%

Multi-criteria analysis of optimal signal plans using microscopic traffic models

Jin

Lei

2014

Transportation Research Part D: Transport and Environment

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Multi-criteria analysis of optimal signal plans using microscopic traffic models. AbstractIncreasing concerns on environment and natural resources, coupled with increasing demand for transport, put lots of pressure for improved efficiency and performance on transport systems worldwide. New technology nowadays enables fast innovation in transport, but it is the policy for deployment and operation with a systems perspective that often determines success. Smart traffic management has played important roles for continuous development of traffic systems especially in urban areas. There is, however, still lack of effort in current traffic management and planning practice prioritizing policy goals in environment and energy. This paper presents an application of a model-based framework to quantify environmental impacts and fuel efficiency of road traffic, and to evaluate optimal signal plans with respect not only to traffic mobility performance but also other important measures for sustainability. Microscopic traffic simulator is integrated with micro-scale emission model for estimation of emissions and fuel consumption at high resolution. A stochastic optimization engine is implemented to facilitate optimal signal planning for different policy goals, including delay, stop-and-goes, fuel economy etc. In order to enhance the validity of the modeling framework, both traffic and emission models are fine-tuned using data collected in a Chinese city. In addition, two microscopic traffic models are applied, and lead to consistent results for signal optimization. Two control schemes, fixed time and vehicle actuated, are optimized while multiple performance indexes are analyzed and compared for corresponding objectives. Solutions, representing compromise between different policies, are also obtained in the case study by optimizing an integrated performance index.

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“…CMEM (Scora and Barth, 2006). Detailed information on vehicle state and emission is therefore required to determine model forms and to estimate model parameters (Rapone et al, 2008). …”

Section: Emission Estimation Modelsmentioning

confidence: 99%

Multi-criteria analysis of optimal signal plans using microscopic traffic models

Jin

Lei

2014

Transportation Research Part D: Transport and Environment

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“…The model is able to calculate emission factor [15] taking into account a large number of parameters to characterize the kinematics of DCs. In the emission modelling context the dimensionality consideration could be probed by PLS (Partial Least Squares) multivariate regression method.…”

Section: Modelling Approachmentioning

confidence: 99%

“…Following previous studies [15,16] two blocks of X variables were identified considering two potential causes of variability in emissions for a driving cycle: energy expenditure from the vehicle in the cycle and the acceleration events at different speeds.…”

Section: Modelling Approachmentioning

confidence: 99%

Evaluation of Emission Factors for New Technology S. I. Euro 4 Cars

Meccariello

Ragione

Costagliola

et al. 2012

CIT

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This research attempted to analyze the environmental impact of two available non-conventional vehicle technologies, highlighting the benefits in terms of emissions and fuel consumption reduction with respect to conventional vehicles. Moreover, tests were compared with predicted emissions of the conventional gasoline technology provided by the kinematic model developed. Results show that cold start strongly affects the emissions of CO, THC and NO X , which become very low during hot driving cycle. The existing emission model cannot be used to obtain a satisfactory prediction for hybrid car. But it could be proved that KEM emission model allows us to predict emission factor for conventional car and compressed natural gas. However, it is concluded that new experimental campaign with new technological cars might be interesting for future model developments.

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“…According to a multi-block approach (MBPLS) [5], a base model 1 is defined for block1 and a base model 2 is calculated for block2 of variables. Then the super block regression model, named top model, is built, making the regression of Y-variables on the union of scores of the two base models.…”

Section: The Core Of Is: the Model Basementioning

confidence: 99%

“…The latest version is 2.1 and dates from February 2004, in which the emission factors of the HDV (heavy duty vehicles) are completely revised and new measurements for all vehicle categories up to EURO3 are included. The kinematic model approach in ARTEMIS was developed by Rapone [5], and it predicts average emissions on a microtrip (driving pattern) obtaining a detailed description of the velocity profile using a multidimensional approach. This kinematic model (Kinematic Emission Model KEM) is defined as a meso-scale emission model, and it is to be pointed out that it may require less detailed information with respect to instantaneous models.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Knowledge Base for Modelling and Predicting Vehicle Real-world Emissions as a Function of Driving Behaviour Kinematics

Rapone¹,

Ragione

Meccariello

2008

CIT

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A multivariate modelling approach was developed by Istituto Motori to model and predict vehicle real-world emissions. Complex driving kinematics is represented by two blocks of variables, which require the development of a hierarchical multiblock emission model, where the two blocks of variables represent overall and instantaneous features of each driving cycle associated to a trip. The multiblock model was applied to analyze and model emissions of the large database built in the ARTEMIS project. In this database we collected emission measurements performed in European laboratories relative to real driving cycles which are statistically representative of many European traffic/road conditions from congested to rush-hour traffic in urban, rural and highway roads. Data concern a varied fleet of vehicles differing in technology and class. To develop a tool useful for mobility analysts for traffic environmental impact assessment, a knowledge base was envisaged to integrate the data warehouse and the model base to build a user interface for driving cycle kinematics and emission analysis. In this paper the modelling approach is presented together with overall emission and driving kinematics characterization based on experimental results, as well as functional analysis of the knowledge base structure and the information tool.

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Emission Factors Determination of Euro III 1,200- to 1,400-cc Petrol Passenger Cars with a PLS Multivariate Regression Model

Cited by 18 publications

References 6 publications

Multi-criteria analysis of optimal signal plans using microscopic traffic models

Multi-criteria analysis of optimal signal plans using microscopic traffic models

Evaluation of Emission Factors for New Technology S. I. Euro 4 Cars

An Integrated Knowledge Base for Modelling and Predicting Vehicle Real-world Emissions as a Function of Driving Behaviour Kinematics

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