scholarly journals Numerical Modeling of Spark Ignition in Internal Combustion Engines

2019 ◽  
Vol 142 (2) ◽  
Author(s):  
Rafał Pyszczek ◽  
Jooyoung Hahn ◽  
Peter Priesching ◽  
Andrzej Teodorczyk
Keyword(s):  
Internal Combustion Engines ◽  
Engine Performance ◽  
Spark Ignition ◽  
Electrical Circuit ◽  
Heat Diffusion ◽  
Combustion Model ◽  
Ignition Process ◽  
Discharge Process ◽  
Proposed Model ◽  
Spark Channel

Abstract In this paper, we aim to develop a comprehensive ignition model for three-dimensional (3D) computational fluid dynamics (CFD) combustion modeling in spark-ignited (SI) engines. In the proposed model, we consider the following aspects separately to model the spark ignition process comprehensively. An electrical circuit is solved for calculation of the energy transferred to the spark plasma channel. The spark itself is represented by computational particles for monitoring its motion and ignitability. Heat diffusion from the spark toward the surrounding mixture is calculated with a one-dimensional (1D) model, resulting in the temperature obtained at the surface of the spark channel. Based on the calculated temperature and interpolated pressure and local mixture composition, an instantaneous ignition delay time is read from tabulated values for every particle representing the spark channel. The final ignitability criterion is defined by a precursor calculated with a zero-dimensional (0D) model, which accounts for the history of changes in spark surface temperature and local mixture properties. As soon as the precursor reaches a threshold value for a given spark channel particle, a flame kernel is introduced at a position of the particle. Flame propagation is generally treated by the G-equation combustion model. Validation is performed by measurements of the spark discharge process in high-velocity flow field and single-cylinder AVL research engine. We demonstrate that the proposed model can correctly reproduce the electrical circuit, spark channel dynamics, and overall engine performance.

scholarly journals Numerical Study of Engine Performance and Emissions for Port Injection of Ammonia into a Gasoline\Ethanol Dual-Fuel Spark Ignition Engine

2021 ◽  
Vol 11 (4) ◽  
pp. 1441
Author(s):  
Farhad Salek ◽  
Meisam Babaie ◽  
Amin Shakeri ◽  
Seyed Vahid Hosseini ◽  
Timothy Bodisco ◽  
...  
Keyword(s):  
Numerical Study ◽  
Combustion Process ◽  
Engine Performance ◽  
Spark Ignition ◽  
Spark Ignition Engine ◽  
Combustion Model ◽  
Dual Fuel ◽  
Spark Ignition Engines ◽  
Performance And Emissions ◽  
Hc Emissions

This study aims to investigate the effect of the port injection of ammonia on performance, knock and NOx emission across a range of engine speeds in a gasoline/ethanol dual-fuel engine. An experimentally validated numerical model of a naturally aspirated spark-ignition (SI) engine was developed in AVL BOOST for the purpose of this investigation. The vibe two zone combustion model, which is widely used for the mathematical modeling of spark-ignition engines is employed for the numerical analysis of the combustion process. A significant reduction of ~50% in NOx emissions was observed across the engine speed range. However, the port injection of ammonia imposed some negative impacts on engine equivalent BSFC, CO and HC emissions, increasing these parameters by 3%, 30% and 21%, respectively, at the 10% ammonia injection ratio. Additionally, the minimum octane number of primary fuel required to prevent knock was reduced by up to 3.6% by adding ammonia between 5 and 10%. All in all, the injection of ammonia inside a bio-fueled engine could make it robust and produce less NOx, while having some undesirable effects on BSFC, CO and HC emissions.

Comparison of Random Forest and Neural Network in Modelling the Performance and Emissions of a Natural Gas Spark Ignition Engine

2021 ◽  
pp. 1-20
Author(s):  
Jinlong Liu ◽  
Qiao Huang ◽  
Christopher Ulishney ◽  
Cosmin E. Dumitrescu
Keyword(s):  
Neural Network ◽  
Random Forest ◽  
Natural Gas ◽  
Internal Combustion Engines ◽  
Engine Performance ◽  
Spark Ignition ◽  
Spark Ignition Engine ◽  
Data Driven ◽  
Ann Model ◽  
Mean Square Errors

Abstract Machine learning (ML) models can accelerate the development of efficient internal combustion engines. This study assessed the feasibility of data-driven methods towards predicting the performance of a diesel engine modified to natural gas spark ignition, based on a limited number of experiments. As the best ML technique cannot be chosen a priori, the applicability of different ML algorithms for such an engine application was evaluated. Specifically, the performance of two widely used ML algorithms, the random forest (RF) and the artificial neural network (ANN), in forecasting engine responses related to in-cylinder combustion phenomena was compared. The results indicated that both algorithms with spark timing, mixture equivalence ratio, and engine speed as model inputs produced acceptable results with respect to predicting engine performance, combustion phasing, and engine-out emissions. Despite requiring more effort in hyperparameter optimization, the ANN model performed better than the RF model, especially for engine emissions, as evidenced by the larger R-squared, smaller root-mean-square errors, and more realistic predictions of the effects of key engine control variables on the engine performance. However, in applications where the combustion behavior knowledge is limited, it is recommended to use a RF model to quickly determine the appropriate number of model inputs. Consequently, using the RF model to define the model structure and then employing the ANN model to improve the model's predictive capability can help to rapidly build data-driven engine combustion models.

scholarly journals Parametric Knocking Performance Investigation of Spark Ignition Natural Gas Engines and Dual Fuel Engines

2020 ◽  
Vol 8 (6) ◽  
pp. 459 ◽  
Author(s):  
La Xiang ◽  
Gerasimos Theotokatos ◽  
Haining Cui ◽  
Keda Xu ◽  
Hongkai Ben ◽  
...  
Keyword(s):  
Natural Gas ◽  
Compression Ratio ◽  
Engine Performance ◽  
Spark Ignition ◽  
Combustion Model ◽  
Dual Fuel ◽  
Ignition Timing ◽  
Natural Gas Engines ◽  
Study Results ◽  
Pilot Fuel

Both spark ignition (SI) natural gas engines and compression ignition (CI) dual fuel (DF) engines suffer from knocking when the unburnt mixture ignites spontaneously prior to the flame front arrival. In this study, a parametric investigation is performed on the knocking performance of these two engine types by using the GT-Power software. An SI natural gas engine and a DF engine are modelled by employing a two-zone zero-dimensional combustion model, which uses Wiebe function to determine the combustion rate and provides adequate prediction of the unburnt zone temperature, which is crucial for the knocking prediction. The developed models are validated against experimentally measured parameters and are subsequently used for performing parametric investigations. The derived results are analysed to quantify the effect of the compression ratio, air-fuel equivalence ratio and ignition timing on both engines as well as the effect of pilot fuel energy proportion on the DF engine. The results demonstrate that the compression ratio of the investigated SI and DF engines must be limited to 11 and 16.5, respectively, for avoiding knocking occurrence. The ignition timing for the SI and the DF engines must be controlled after −38°CA and 3°CA, respectively. A higher pilot fuel energy proportion between 5% and 15% results in increasing the knocking tendency and intensity for the DF Engine at high loads. This study results in better insights on the impacts of the investigated engine design and operating settings for natural gas (NG)-fuelled engines, thus it can provide useful support for obtaining the optimal settings targeting a desired combustion behaviour and engine performance while attenuating the knocking tendency.

scholarly journals Development of a Hybrid Lagrangian–Eulerian Model to Describe Spark-Ignition Processes at Engine-Like Turbulent Flow Conditions

2019 ◽  
Vol 141 (9) ◽  
Author(s):  
Riccardo Scarcelli ◽  
Anqi Zhang ◽  
Thomas Wallner ◽  
Sibendu Som ◽  
Jing Huang ◽  
...  
Keyword(s):  
Energy Deposition ◽  
Combustion Process ◽  
Spark Ignition ◽  
Computational Time ◽  
Ignition Process ◽  
Time Step ◽  
Eulerian Model ◽  
Constant Volume Chamber ◽  
Spark Channel ◽  
Deposition Models

With the engine technology moving toward more challenging (highly dilute and boosted) operation, spark-ignition processes play a key role in determining flame propagation and completeness of the combustion process. On the computational side, there is plenty of spark-ignition models available in literature and validated under conventional, stoichiometric spark ignition (SI) operation. Nevertheless, these models need to be expanded and developed on more physical grounds since at challenging operation they are not truly predictive. This paper reports on the development of a dedicated model for the spark-ignition event at nonquiescent, engine-like conditions, performed in the commercial CFD code converge. The developed methodology leverages previous findings that have expanded the use and improved the accuracy of Eulerian-type energy deposition models. In this work, the Eulerian energy deposition is coupled at every computational time-step with a Lagrangian-type evolution of the spark channel. Typical features such as spark channel elongation, stretch, and attachment to the electrodes are properly described to deliver realistic energy deposition along the channel during the entire ignition process. The numerical results are validated against schlieren images from an optical constant volume chamber and show the improvement in the simulation of the spark channel during the entire ignition event, with respect to the most commonly used energy deposition approach. Further developmental pathways are discussed to provide more physics-based features from the developed ignition model in the future.

A New Single-Zone Multi-Stage Scavenging Model for Real-Time Emissions Control in Two-Stroke Engines

2019 ◽  
Author(s):  
Abdullah U. Bajwa ◽  
Mark Patterson ◽  
Taylor Linker ◽  
Timothy J. Jacobs
Keyword(s):  
Gas Exchange ◽  
Internal Combustion Engines ◽  
Engine Performance ◽  
Combustion Engines ◽  
Thermodynamic State ◽  
Multi Stage ◽  
Exchange Processes ◽  
Proposed Model ◽  
Perfect Mixing ◽  
And Control

Abstract Gas exchange processes in two-stroke internal combustion engines, i.e. scavenging, remove exhaust gases from the combustion chamber and prepare the fuel-oxidizer mixture that undergoes combustion. A non-negligible fraction of the mixture trapped in the cylinder at the conclusion of scavenging is composed of residual gases from the previous cycle. This can cause significant changes to the combustion characteristics of the mixture by changing its composition and temperature, i.e. its thermodynamic state. Thus, it is vital to have accurate knowledge of the thermodynamic state of the post-scavenging mixture to be able to reliably predict and control engine performance, efficiency and emissions. Several simple-scavenging models can be found in the literature that — based on a variety of idealized interaction modes between incoming and cylinder gases — calculate the state of the trapped mixture. In this study, boundary conditions extracted from a validated 1-D predictive model of a single-cylinder two-stroke engine are used to gauge the performance of four simple scavenging models. It is discovered that the assumption of thermal homogeneity of the incoming and exiting gases is a major source of inaccuracy. A new non-isothermal multi-stage single-zone scavenging model is thus, proposed to address some of the shortcomings of the four models. The proposed model assumes that gas-exchange in cross-scavenged two-stroke engines takes place in three stages; an isentropic blowdown stage, followed by perfect-displacement and perfect-mixing stages. Significant improvements in the trapped mixture state estimates were observed as a result.

scholarly journals Development of a Hybrid Lagrangian-Eulerian Model to Describe Spark-Ignition Processes at Engine-Like Turbulent Flow Conditions

2018 ◽  
Author(s):  
Riccardo Scarcelli ◽  
Anqi Zhang ◽  
Thomas Wallner ◽  
Sibendu Som ◽  
Jing Huang ◽  
...  
Keyword(s):  
Energy Deposition ◽  
Combustion Process ◽  
Spark Ignition ◽  
Computational Time ◽  
Ignition Process ◽  
Time Step ◽  
Eulerian Model ◽  
Constant Volume Chamber ◽  
Spark Channel ◽  
Further Development

With the engine technology moving towards more challenging (highly dilute and boosted) operation, spark-ignition processes play a key role in determining flame propagation and completeness of the combustion process. On the computational side, there is plenty of spark-ignition models available in literature and validated under conventional, stoichiometric SI operation. Nevertheless, these models need to be expanded and developed on more physical grounds since at challenging operation they are not truly predictive. This paper reports on the development of a dedicated model for the spark-ignition event at non-quiescent, engine-like conditions, performed in the commercial CFD code CONVERGE. The developed methodology leverages previous findings that have expanded the use and improved the accuracy of Eulerian-type energy deposition models. In this work, the Eulerian energy deposition is coupled at every computational time-step with a Lagrangian-type evolution of the spark channel. Typical features such as spark channel elongation, stretch, attachment to the electrodes are properly described to deliver realistic energy deposition along the channel during the entire ignition process. The numerical results are validated against schlieren images from an optical constant volume chamber and show the improvement in the simulation of the spark channel during the entire ignition event, with respect to the most commonly used energy deposition approach. Further development pathways are discussed to provide more physics-based features from the developed ignition model in the future.

scholarly journals Analysis of Engine Performance Parameters with Hydrogen Enrichment in Premixed Spark Ignition Engine Using Fuel Blend

2021 ◽  
Vol 4 (2) ◽  
Keyword(s):  
Internal Combustion Engines ◽  
Engine Performance ◽  
Spark Ignition ◽  
Independent Study ◽  
Spark Ignition Engine ◽  
Gasoline Direct Injection ◽  
Pure Hydrogen ◽  
Cylinder Pressure ◽  
Performance Parameters ◽  
Hydrogen Enrichment

Hydrogen enrichment in internal combustion engines has been a topic of research interest to improve engine efficiencies and reduce carbon emissions. Hydrogen enrichment has garnered more interest than the pure hydrogen powered engines due to less complexity involved with the modifications of the engine and fuel system as well as the infrastructure required for it. Similarly, accurate chemical kinetics has proved to provide accurate results in terms of engine performance parameters, such as, in-cylinder pressure. The present study is an extension of study performed earlier with hydrogen enrichment in gasoline direct injection engine while using C8 H17 as a surrogate fuel for gasoline and assumes that an on-board electrolysis system installed on the vehicle produces hydrogen for the enrichment purposes. A mesh independent study is performed using 90% iso-octane (iC8 H18) and 10% n-heptane (nC7 H16) blend as a gasoline surrogate with hydrogen enrichment of 0%, 1%, 2% and 3% at equivalence ratios of 0.98 and 1.3, in a premixed spark ignition engine. Numerical simulations are performed to calculate and compare the thermal and combustion efficiencies of the engine using hydrogen-enriched fuel versus iso-octane and n-heptane blend. The study also predicts and measures the engine performance parameter of in-cylinder pressure, while comparing the iso-octane and n-heptane blend against the blend enriched with hydrogen. Based on the results obtained from smaller hydrogen enrichment concentrations, the study increases the hydrogen-enrichment of the fuel to 5%, 10% and 15% to analyse the effects of enrichment on the thermal and combustion efficiencies, as well as the in-cylinder pressure.

High-Fidelity Energy Deposition Ignition Model Coupled With Flame Propagation Models at Engine-Like Flow Conditions

2021 ◽  
Author(s):  
Samuel J. Kazmouz ◽  
Riccardo Scarcelli ◽  
Joohan Kim ◽  
Zhen Cheng ◽  
Shuaishuai Liu ◽  
...  
Keyword(s):  
Flame Propagation ◽  
Energy Deposition ◽  
Spark Ignition ◽  
Grid Size ◽  
High Fidelity ◽  
Ignition Process ◽  
Time Step ◽  
Engine Operation ◽  
Propagation Models ◽  
Spark Channel

Abstract With the heightened pressure on car manufacturers to increase the efficiency and reduce the carbon emissions of their fleets, more challenging engine operation has become a viable option. Highly dilute, boosted, and stratified charge, among others, promise engine efficiency gains and emissions reductions. At such demanding engine conditions, the spark-ignition process is a key factor for the flame initiation propagation and the combustion event. From a computational standpoint, there exists multiple spark-ignition models that perform well under conventional conditions but are not truly predictive under strenuous engine operation modes, where the underlying physics needs to be expanded. In this paper, a hybrid Lagrangian-Eulerian spark-ignition (LESI) model is coupled with different turbulence models, grid sizes, and combustion models. The ignition model, previously developed, relies on coupling Eulerian energy deposition with a Lagrangian particle evolution of the spark channel, at every time-step. The spark channel is attached to the electrodes and allowed to elongate at a speed derived from the flow velocity. The LESI model is used to simulate spark ignition in a non-quiescent crossflow environment at engine-like conditions, using CONVERGE commercial CFD solver. The results highlight the consistency, robustness, and versatility of the model in a range of engine-like setups, from typical with RANS and a larger grid size to high fidelity with LES and a finer grid size. The flame kernel growth is then evaluated against schlieren images from an optical constant volume ignition chamber with a focus on the performance of flame propagation models, such as G-equation and thickened flame model, versus the baseline well-stirred reactor model. Finally, future development details are discussed.

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