Cycle-by-Cycle Analysis of Cold Crank-Start in a GDI Engine

Rodriguez, J. Felipe; Cheng, Wai K.

doi:10.4271/2016-01-0824

Cited by 25 publications

(10 citation statements)

References 22 publications

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“…The issue becomes more pronounced under cold-start conditions when multiple injection strategies are implemented. 8,9 The variations in the local properties at the spark plug locations play a significant role in the growth of the initial kernel established by the spark, and its subsequent evolution into a turbulent flame. To accurately model the DISI combustion process, it is important to account for the effects of the spark ignition process.…”

Section: Introductionmentioning

confidence: 99%

G-equation based ignition model for direct injection spark ignition engines

Ravindran

Kokjohn

Petersen

2021

International Journal of Engine Research

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To accurately model the Direct Injection Spark Ignition (DISI) combustion process, it is important to account for the effects of the spark energy discharge process. The proximity of the injected fuel spray and spark electrodes leads to steep gradients in local velocities and equivalence ratios, particularly under cold-start conditions when multiple injection strategies are employed. The variations in the local properties at the spark plug location play a significant role in the growth of the initial flame kernel established by the spark and its subsequent evolution into a turbulent flame. In the present work, an ignition model is presented that is compatible with the G-Equation combustion model, which responds to the effects of spark energy discharge and the associated plasma expansion effects. The model is referred to as the Plasma Velocity on G-surface (PVG) model, and it uses the G-surface to capture the early kernel growth. The model derives its theory from the Discrete Particle Ignition (DPIK) model, which accounts for the effects of electrode heat transfer, spark energy, and chemical heat release from the fuel on the early flame kernel growth. The local turbulent flame speed has been calculated based on the instantaneous location of the flame kernel on the Borghi-Peters regime diagram. The model has been validated against the experimental measurements given by Maly and Vogel,1 and the constant volume flame growth measurements provided by Nwagwe et al.2 Multi-cycle simulations were performed in CONVERGE3 using the PVG ignition model in combination with the G-Equation-based GLR4 model in a RANS framework to capture the combustion characteristics of a DISI engine. Good agreements with the experimental pressure trace and apparent heat-release rates were obtained. Additionally, the PVG ignition model was observed to substantially reduce the sensitivity of the default G-sourcing ignition method employed by CONVERGE.

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Section: Introductionmentioning

confidence: 99%

G-equation based ignition model for direct injection spark ignition engines

Ravindran

Kokjohn

Petersen

2021

International Journal of Engine Research

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“…4 Within this cold-start phase, the early engine crank-start followed by approximately 20 seconds of the cold-start, fast-idle (catalyst heating) phase is responsible for the major share of emissions. 5,6 To address the cold-start emissions issue, many engines use a split injection strategy, where the first injection takes place during the intake, while the second injection takes place during the compression stroke. It was shown that for a delayed ignition time, this strategy can generate stratified local enrichment around the spark plug, and can, therefore, improve the combustion stability and reduce emissions compared to the single injection strategy.…”

Section: Introductionmentioning

confidence: 99%

Improving computational fluid dynamics modeling of Direct Injection Spark Ignition cold-start

Ravindran

Kokjohn

Petersen

2020

International Journal of Engine Research

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Developing a profound understanding of the combustion characteristics of the cold-start phase of a Direct Injection Spark Ignition (DISI) engine is critical to meeting increasingly stringent emissions regulations. Computational Fluid Dynamics (CFD) modeling of gasoline DISI combustion under normal operating conditions has been discussed in detail using both the detailed chemistry approach and flamelet models (e.g. the G-Equation). However, there has been little discussion regarding the capability of the existing models to capture DISI combustion under cold-start conditions. Accurate predictions of cold-start behavior involves the efficient use of multiple models - spray modeling to capture the split injection strategies, models to capture the wall-film interactions, ignition modeling to capture the effects of retarded spark timings, combustion modeling to accurately capture the flame front propagation, and turbulence modeling to capture the effects of decaying turbulent kinetic energy. The retarded spark timing helps to generate high heat flux in the exhaust for the faster catalyst light-off during cold-start. However, the adverse effect is a reduced turbulent flame speed due to decaying turbulent kinetic energy. Accordingly, developing an understanding of the turbulence-chemistry interactions is imperative for accurate modeling of combustion under cold-start conditions. In the present work, combustion characteristics during the cold-start, fast-idle phase is modeled using the G-Equation flamelet model and the RANS turbulence model. The challenges associated with capturing the turbulent-chemistry interactions are explained by tracking the flame front travel along the Borghi-Peters regime diagram. In this study, a modified version of the G-Equation combustion model for capturing cold-start flame travel is presented.

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“…A nivel mundial se emiten leyes para regular la cantidad de contaminantes emitidos por los motores de combustión a la atmósfera, razón por la cual los fabricantes han desarrollado nuevas tecnologías como vehículos híbridos y eléctricos, pero debido a que este tipo de tecnología todavía no satisface completamente las expectativas de los consumidores, se han visto en la necesidad de desarrollar nuevas tecnologías usando combustibles fósiles, como la inyección directa a gasolina, con el objetivo de cumplir estas normas. Esta tecnología se comercializa en todo el mundo e introduce nuevos conceptos y elementos, además de rediseñar el funcionamiento de algunos elementos ya utilizados en los sistemas tradicionales de inyección indirecta a gasolina los cuales se manifiestan con respecto al ingreso de aire, el suministro de combustible, el salto de chispa y la emisión de gases contaminantes (Rodríguez and Cheng, 2016); (C. Huang et al, 2016). Pero la variación del funcionamiento de los distintos elementos depende del modo de trabajo seleccionado por el módulo de control electrónico, por esto la importancia de conocer la selección del modo de trabajo ya que no hay ningún indicador o parámetro de identificación en la línea de datos que indique el modo de trabajo que se está ejecutando.…”

Section: Introductionunclassified

Estratificación de un motor de inyección directa a gasolina al variar la altitud.//Stratification of a gasoline direct injection to vary altitude.

Leguísamo-Milla

Celi-Ortega²,

Cedeño³

et al. 2019

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En este artículo se desarrolla una metodología experimental con el objeto de determinar la estratificación de la mezcla aire- combustible que se produce en un motor de inyección directa a gasolina, que puede ser homogénea, homogénea pobre y estratificada. Al variar el nivel de altura geográfica en el vehículo de 0 a 4000 metros de altura con respecto al nivel del mar. Determinando cuáles son los parámetros que inciden directamente en la estratificación de la mezcla aire combustible conocidos como modo de trabajo, mediante el estudio del sistema GDI y la aplicación de una prueba experimental dinámica en base a normas y protocolos desarrolladas por la SAE. Utilizando un escáner automotriz de última generación y un GPS, aplicados a un vehículo MAZDA CX-5. Los resultados de las pruebas realizadas revelan cuando se producen los modos de trabajo homogéneo pobre, homogéneo y estratificado en las pruebas. Además, indican cómo influye la variación de la altura en la selección de estos modos de trabajo cada 500 metros de altura y muestran cómo se puede identificar cada modo de trabajo con el escáner mediante la línea de datos, y entender los cambios en el funcionamiento debido a la variación del modo de trabajo. AbstractIn this article an experimental methodology is developed in order to determine the stratification of the air-fuel mixture produced in a gasoline direct injection engine, which can be homogeneous, lean homogeneous and stratified. By varying the level of geographical height in the vehicle from 0 to 4000 meters above sea level. Determining which are the parameters that directly affect the stratification of the fuel air mixture known as working mode, through the study of the GDI system and the application of a dynamic experimental test based on standards and protocols developed by the SAE. Using an automotive scanner of last generation and a GPS, applied to a MAZDA CX-5 vehicle. The results of the tests carried out reveal when poor homogeneous, homogeneous and stratified working modes are produced in the tests. In addition, they show how height variation influences the selection of these working modes every 500 metres in height and show how each working mode can be identified with the scanner via the data line, and understand the changes in operation due to variation in working mode.

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Cycle-by-Cycle Analysis of Cold Crank-Start in a GDI Engine

Cited by 25 publications

References 22 publications

G-equation based ignition model for direct injection spark ignition engines

G-equation based ignition model for direct injection spark ignition engines

Improving computational fluid dynamics modeling of Direct Injection Spark Ignition cold-start

Estratificación de un motor de inyección directa a gasolina al variar la altitud.//Stratification of a gasoline direct injection to vary altitude.

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