Development and Application of a Semi-Empirical NOx Model to Various HD Diesel Engines

Gärtner, Uwe; Hohenberg, Günter; Daudel, H. L.; Oelschlegel, H.

doi:10.1007/978-3-662-10502-3_14

Cited by 16 publications

(9 citation statements)

References 5 publications

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“…Some variations of the present procedure have been encountered by: Komiyama and Heywood [50], Nightingale [42], Bowman [51] and Kyriakides et al [52]. These are mainly related with neglecting the effect of the N 2 O pathway or even by discarding all reactions except: N+NO=N 2 +O and N+O 2 =NO+O, [53][54] With respect to the thermal NO, predominant in CDC conditions, in-cylinder parameters (capable of describing the evolution of the combustion process) and/or the flame temperature data (dependent on the air temperature and the oxygen concentration) have been related to this mechanism to predict the NO engine-out emissions.…”

Section: 311equilibrium Conditionsmentioning

confidence: 99%

The role of detailed chemical kinetics on CFD diesel spray ignition and combustion modelling

Novella

García

Pastor

et al. 2011

Mathematical and Computer Modelling

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A mis padres, Josep y Empar, porque han estado siempre presentes en todas las dificultades que enfrenté. Os debo mucho porque sois ejemplos de carácter, esfuerzo, cariño y dedicación. A mi hermano Carles que es una gran persona, que merece mucho la pena, y que es un compañero de infatigables aventuras. A mi mujer Maria José que ha estado a mi lado todo este tiempo, ayudándome durante el doctorado, con su dedicación, cariño y paciencia. Gracias por tu optimismo. Mi hijo Pau que ha sido una fuente de inspiración, de diversión y una bocanada de aire fresco.

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Section: 311equilibrium Conditionsmentioning

confidence: 99%

The role of detailed chemical kinetics on CFD diesel spray ignition and combustion modelling

Novella

García

Pastor

et al. 2011

Mathematical and Computer Modelling

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“…The CMEM predicts emissions well, but may underestimate them for highemitting vehicles because the model is based on the average data of 300 vehicles (including about 30 high emitters) measured during dynamometer tests, along different driving cycles (Rakha et al, 2003). Another model proposed by Gärtner et al (2004) estimates emissions from fuel consumption at engine mechanics level. The model relies on the first Law of Thermodynamics and chemical kinetic reaction rate considerations.…”

Section: Deterministic Methodsmentioning

confidence: 99%

Ecological traffic management: A review of the modeling and control strategies for improving environmental sustainability of road transportation

Othman

Nunzio

Domenico

et al. 2019

Annual Reviews in Control

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As road transportation energy use and environmental impact are globally rising at an alarming pace, authorities seek in research and technological advancement innovative solutions to increase road traffic sustainability. The unclear and partial correlation between road congestion and environmental impact is promoting new research directions in traffic management. This paper aims to review the existing modeling approaches to accurately represent traffic behavior and the associated energy consumption and pollutant emissions. The review then covers the transportation problems and control strategies that address directly environmental performance criteria, especially in urban networks. A discussion on the advantages of the different methods and on the future outlook for the eco-traffic management completes the proposed survey.

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“…The cold-start effect is therefore captured with a model that estimates the engine temperature at each time step. One of the main contributions of this work is the NO x emissions models for Diesel engines which is inspired from a semi-empirical model presented in [39]. The original model was:…”

Section: Engine-out Emissions Modelmentioning

confidence: 99%

Road Traffic Dynamic Pollutant Emissions Estimation: From Macroscopic Road Information to Microscopic Environmental Impact

2020

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Air pollution poses a major threat to health and climate, yet cities lack simple tools to quantify the costs and effects of their measures and assess those that are most effective in improving air quality. In this work, a complete modeling framework to estimate road traffic microscopic pollutant emissions from common macroscopic road and traffic information is proposed. A machine learning model to estimate driving behavior as a function of traffic conditions and road infrastructure is coupled with a physics-based microscopic emissions model. The up-scaling of the individual vehicle emissions to the traffic-level contribution is simply performed via a meta-model using both statistical vehicles fleet composition and traffic volume data. Validation results with real-world driving data show that: the driving behavior model is able to maintain an estimation error below 10% for relevant boundary parameter of the speed profiles (i.e., mean, initial, and final speed) on any road segment; the traffic microscopic emissions model is able to reduce the estimation error by more than 50% with respect to reference macroscopic models for major pollutants such as NOx and CO2. Such a high-resolution road traffic emissions model at the scale of every road segment in the network proves to be highly beneficial as a source for air quality models and as a monitoring tool for cities.

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Development and Application of a Semi-Empirical NOx Model to Various HD Diesel Engines

Cited by 16 publications

References 5 publications

The role of detailed chemical kinetics on CFD diesel spray ignition and combustion modelling

The role of detailed chemical kinetics on CFD diesel spray ignition and combustion modelling

Ecological traffic management: A review of the modeling and control strategies for improving environmental sustainability of road transportation

Road Traffic Dynamic Pollutant Emissions Estimation: From Macroscopic Road Information to Microscopic Environmental Impact

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