Natural Gas Spark Ignition Engine Research Articles

Effects of gas injection timing on combustion instability for a spark ignition natural gas engine under low load conditions

• The entire cycle of in-cylinder pressure time series is applied to study the CCV. • The return maps and phase space reconstruction are used as the analysis methods. • The gas injection timing is used as the impact factor. • The chaotic behavior is stronger when the GIT is near 60°CA ATDC. Experiments are carried out with different GITs under 10% and 25% load conditions to reveal the influence of gas injection timing (GIT) on combustion instability for a spark ignition natural gas engine under low load conditions. The phase space reconstruction and coefficient of cyclic variation (CCV) of the entire cycle in-cylinder pressure time series, the return maps of indicated mean effective pressure (IMEP) and CA50, the distributions of CA5 and CA90 are applied to analyze the combustion instability of the natural gas engine qualitatively and quantitatively. Results show that the combustion process of the natural gas engine presents chaotic characteristics. With increasing GIT from 0°CA to 90°CA ATDC, the CCV and the separation degree of phase space attractor initially increase and then decrease. The distributions of return map points for IMEP and CA50 initially disperse and then concentrate, and the combustion instability and chaotic characteristics are initially enhanced and then weaken. When the GIT is near 60°CA ATDC, the chaotic characteristics of combustion instability for the natural gas engine is the strongest. The reasons for the influence of GIT on combustion instability of the natural gas engine are identified based on 3D computational fluid dynamic (CFD) simulation, showing that the pressure difference between in-cylinder and the intake manifold under different GITs leads to the difference in the mixing degree of the natural gas and air as well as the CH 4 concentration distribution of in-cylinder. This finding provides a theoretical basis for improving the lean-burn stability of natural gas engines.

A 0/1-Dimensional Numerical Analysis of Performance and Emission Characteristics of the Conversion of Heavy-Duty Diesel Engine to Spark-Ignition Natural Gas Engine

Increasing air pollution has brought about the search for alternative fuels instead of conventional fuels. It is aimed to make existing internal combustion engines work with alternative fuels with the least structural changes. Natural gas (NG) is one of the most recent alternative fuel studies because it is both cheaper and more environmen-tally friendly. In this study, it was aimed to minimize the dependence on petroleum-based fuels by enabling an existing compression ignition (CI) engine to operate with spark ignition with NG. For this reason, in heavy-duty diesel engine; It was modeled as 0/1-dimensional with spark plug assembly instead of diesel injector and low-pressure NG fuel injector mounted on the intake manifold. Afterwards, the perfor-mance, combustion characteristics, and emission values of the engine, which were converted to NG, were compared with the experimentally validated diesel model. In addition to the comparisons made under similar conditions, the effects of start of combustion (SOC) time and Air/Fuel (A/F) ratio changes in NG use were performed parametrically. In the same conditions, it was observed that the power, fuel con-sumption, and efficiency of the engine increased in NG fuel use compared to diesel fuel use. However, with the parametric studies in NG use, an improvement of 84.5% was achieved in NOX emission without any performance loss compared to diesel use.

Three-Dimensional Computational Fluid Dynamics Simulation and Mesh Size Effect of the Conversion of a Heavy-Duty Diesel Engine to Spark-Ignition Natural Gas Engine

Abstract With developing in computer technology, three-dimensional (3D) computational fluid dynamics (CFD) internal combustion (IC) engine simulations, which generally use reduced chemical kinetic mechanisms and simplified combustion models, can provide more accurate results along with less initial investment and calculation costs compared to experimental setup. In this study, a heavy-duty diesel engine effects on performance, combustion, and emission characteristics by spraying natural gas from the intake port and transforming it into a spark-ignition engine were investigated through 3D ansysfortecfd program. The spark time was accepted as 0.5 °CA before top dead center (bTDC), which was the start of injection time for the diesel injector. Analyzes were carried out at 2300 rpm, full load, 17.5: 1 of high compression ratio, constant air/fuel ratio. Six different global mesh sizes were used in the converted engine model. Performance, in-cylinder combustion, and emission values were examined for these six different global mesh sizes and the most suitable one was tried to be found. As a result of the global mesh size study, it was concluded that the most suitable size was 2.25 mm. In terms of performance, when the data obtained with usage of natural gas were compared to that of diesel fuel, the gross indicated power (GIP), indicated mean effective pressure (IMEP), and indicated thermal efficiency (ITE) values were increased by 12.02%, 8.93%, and 8.7%, respectively, while the gross indicated specific fuel consumption (GISFC) value was decreased by 9.78%. When the emission values were examined, it was seen that the engine met the stage IIIB norms without usage of selective catalytic reduction (SCR), diesel particulate filter (DPF), and diesel oxidation catalyst (DOC) under the conditions.

A Study on the Correlation of Factors Influencing the Cyclic Variation of Marine Natural Gas Engines

As the most reliable alternative energy source for traditional fuel engines, natural gas has been widely used in inland river marine engines. The natural gas engine is faced with the problem of increased cyclic variations under the condition of lean combustion. In this paper, a multi-point injection spark ignition natural gas engine is tested under different lean burn degrees to investigate the correlation between different parameters and cyclic variation, including accumulated heat release, combustion phase and burning rate. The purpose is to clarify the optimized technical route for marine natural gas engine. A new method to quantify the correlation between parameters and cyclic variation is proposed. The maximum explosion pressure of combustion and its phase are used as the parameters to characterize the cyclic variation. Different parameters are then nonlinearly fitted to it, and the R-S value of the fitting is used to quantify the correlation between parameters and cyclic variation. The results show that the correlation between accumulated heat release and cyclic variation is less than 10%. The main factors causing the cyclic variation are the fluctuation of ignition delay and initial flame propagation, whose correlation with cyclic variation is over 80% and 70%, respectively.

Colorless distributed combustion (CDC) effects on a converted spark-ignition natural gas engine

This study examines combustion and emission characteristics of a converted-engine, which suggests that a diesel engine with high compression ratio is transformed to a spark-ignition engine through natural gas addition coming from the intake port. The pollutant emissions such as NOX for the converted-engine pollutant is generally higher than that of a diesel-engine along with higher in-cylinder temperature. Those challenges can be overcome through new and novel combustion methods such as colorless distributed combustion (CDC). Colorless distributed combustion is a method that provides ultra-low pollutant emissions, a more uniform thermal field and reduced combustion noise along with mitigated flame instability. CDC is basically achieved by reducing oxygen concentration in the oxidizer. That decrease can be provided with recirculation of hot combustion products into the oxidizer. In order to achieve CDC, N2 as the diluent was entrained into the fuel-oxidizer mixture from 23 % to 13 % O2 concentrations by mass. The converted-engine representing a tractor engine operated at 2300 rpm and full load was investigated numerically to obtain its performance, combustion and emission characteristics under CDC conditions through ANSYS Forte 3-Dimensional analysis program. G-equation combustion model with methane chemical kinetic mechanism consisting of 29 species and 171 equations, and RANS k-e turbulence model were selected for all modelings. According to the results predicted, it is demonstrated that for the converted engine there has been an improvement of up to 29% in terms of performance. In addition, it is concluded that a 97.66% decrease in NOX emission has been achieved without reducing the combustion performance of the converted engine under CDC.

Exhaust emissions from a prototype non-road natural gas engine

Since gas engines are considered a future solution to improve air quality and to mitigate climate impacts, there is an urgent need to understand their emissions. The aim for this study was to understand the phenomena affecting the formation of particulate emissions of a non-road natural gas engine. To achieve this, the engine’s exhaust emissions were characterized under different operating conditions. The regulated pollutants (gaseous CO, HC, and NOx; particulate matter (PM) and particle number (PN)) were determined experimentally and a detailed characterization of particulate pollutants over a wide particle size range (particles down to 1.2 nm) was conducted with state-of-the-art instrumentation considering both physical and chemical properties of the exhaust aerosol. The test engine was a prototype non-road spark-ignited natural gas engine, which was studied over the non-road steady test cycle (NRSC). The role of the three-way catalyst (TWC) was studied by sampling and characterizing the exhaust aerosol both with and without the TWC. The TWC was observed to efficiently remove the vast majority of the regulated gaseous (96% CO, 98% HC, 98% NOx) and particulate mass emissions (98%). In general, the measured particle number emission factors were highly dependent on the cut-off sizes of the condensation particle counters. Using CPCs with smaller cut-off sizes resulted in higher particle number emission factors. For black carbon (BC), the intermediate engine speed conditions (modes 5–7) led to lower BC emissions than the high speed conditions (modes 1–3). In contrast, highest BC emissions on a work basis were observed during idling. TWC did not influence BC levels. Without the TWC, PM was comprised mostly of organic compounds (70–100%). Downstream of the TWC, the majority of PM was, depending on the load, composed of organic compounds, sulfate, or black carbon. A statistical source apportionment based on mass spectra revealed that the PM1 was mostly related to unburned and burned lubricating oil, indicating a minor role of fuel in PM formation.

An experimental investigation on performance of converted CNG engine by varying piston bowl geometry: A case study

ABSTRACT Using natural gas as an alternative fuel will be reduced exhaust emissions and dependence on petroleum. The practical solution for Vietnam’s conditions is to convert diesel engines into natural gas engines. Understanding the effect of piston geometry on the performance of converted CNG engines helps domestic manufacturers come up to spark ignition natural gas engines with high performance and low emission. In this work, three different types of combustion chamber were made from milling piston head and varying thickness of cylinder head gasket. The experiment results showed that torque and power of ε = 11.5 were more significant than ε = 12.5. During experiment processes, the stable operation state of the converted engine with ε = 12.5 was challenging to control, and the noise levels were intense. The results of mass fraction burned were presented the effect of squish gap on performance was more substantial than that of the squish area. It can be concluded that for modifying the original diesel engines to run on CNG fuel, the maximum compression ratio should be set to 12.5 and must be redesigned accordingly to use the natural results. Implications: This manuscript shows the new technology to convert traditional engines into engines fueled by renewable energy. It contributes to reducing the fossil fuel crisis and environmental emissions.

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

Abstract Machine learning (ML) models can accelerate the development of efficient internal combustion engines. This study assessed the feasibility of data-driven methods toward predicting the performance of a diesel engine modified to natural gas (NG) spark ignition (SI), 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 (ST), 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 (RMSEs), 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 using the ANN model to improve the model’s predictive capability can help to rapidly build data-driven engine combustion models.

Quantitative analysis of engine parameters of a variable compression ratio CNG engine using machine learning

The numerical ability of machine learning methods has been a base in different engineering fields, including internal combustion engines. The presented study on machine learning methods originated to predict the performance, combustion, and emission characteristics of dedicated compressed natural gas (CNG) spark ignition (SI) engines. The experiments were conducted at various engine loads (IMEP), speeds, and compression ratios (CR) to collect the model training and testing data. The test results showed that with the increase in engine load, speed and CR, the ITE increased by 25%, 5.7%, and 10%, respectively. Similarly, the ISFC decreased about 20%, 9%, and 5.4%, increasing load, CR, and speed, respectively. The in-cylinder pressure, maximum rate of pressure rise, and maximum heat release rate reduces with an increase in engine speed and increases with an increase in CR. The combustion performance, such as flame development angle (FDA) and combustion duration (CD), reduced with an increase in CR. With increasing engine load, speed, and CR, ISCO and ISHC emissions decreased. On the other hand, the ISCO2 emission increased as the engine rpm, and CR increased. A maximum CR of 16 was used during the experiment. Three different machine learning methods (Regression Model, Support Vector Machine (SVM), Artificial Neural Network (ANN)) were used and compared to predict engine performance, combustion, and emission characteristics. Different order regression models and ANN models were tested using a back-propagation algorithm. The ANN and SVM model has been trained using hyperbolic transfer activation function and nonlinear kernel function. The value of correlation coefficient (R) and root mean square error (RMSE) for each output parameter was calculated and compared for three models. The regression model of 3rd order predicted well for ITE, CD, ISHC, ISCO, and ISCO2. Whereas, ANN model accurately predicted Pmax and Rmax. The coefficient of determination (R2) was calculated and compared for three models showing the ANN model suitable for accurate prediction compared to all other test models. The developed model showed excellent results for the prediction of the engine performance, combustion and emission characteristics.

Experimental analysis of the EGR rate and temperature impact on combustion and emissions characteristics in a heavy-duty NG engine

Cooled exhaust gas recirculation (EGR) is one of the most effective methods in spark ignition (SI) natural gas (NG) engines to improve the fuel economy and reduce the nitrogen oxides (NOx) emissions. The objective of this study is to anatomize the EGR rate and temperature impact on the combustion and emissions characteristics by the experiments in a heavy duty (HD) NG engine under various spark timings. The results showed that the increasing EGR rate reduced the burning rate and extended the combustion duration. Spark timing should be optimized to copy with the retarded combustion phase. Under high EGR rate, the combustion performance could be optimized with the increase of EGR temperature. There exists a proper EGR rate in real application for the fuel consumption of the engine. Higher EGR temperature plays positive effects on fuel economy, owing to the higher combustion efficiency and lower throttle losses, and the decreasing amplitude of BSFC is 1.25% between the EGR temperatures of 333 K and 373 K. With the increase of EGR rate from 5% to 25%, NOx emissions are reduced by up to 76%, the unburned hydrocarbon (HC) and carbon monoxide (CO) emissions are increased by 34.6% and 12.9% respectively. Higher EGR temperature could alleviate the increase of HC and CO emissions, but sacrificing the NOx emissions, and the increase extent of NOx emissions is 35.3%. The results provide an insight into the quantitative comparisons of EGR rate and temperature on the NG engine performance and emissions, which promotes the utilizing EGR strategy in SI NG engines.

Effects of direct water injection timings on knock suppression, combustion, and emission performance of high compression ratio hydrogen-enriched natural gas engine

In this study, an approach of direct water injection was applied to suppress knock in the high compression ratio (CR) hydrogen-enriched natural gas (NG) engine. A CFD model for the high CR hydrogen-enriched NG engine was established and its effectiveness was verified by experimental data. On this basis, effects of water injection (WI) timings on knock mitigation, combustion, and emission features of the hydrogen-enriched NG engine were studied in detail. Results show that due to the slower flame propagation speed, monitoring points No.3 and 4 (the area near the intake valve) is more likely to knock accompanied by the higher flow velocity and turbulent kinetic energy. Besides, with the advance of WI timing, KI (knock intensity) keeps nearly unchanged firstly and then has a little increase after the second phase of reduction, whose minimum occurs at −150 °CA. Meanwhile, IMEP, CA10-90, and indicated thermal efficiency (ITE) have a similar change tendency with the maximum at −150 °CA, and ITE reaches its peak of about 40.9% with an increment of 3%. From −30 °CA to −180 °CA, NOx decreases a lot, while HC and CO emissions increase to some extent. Therefore, proper WI timing can not only effectively reduce KI and NOx emission, but also improve thermal efficiency and realize high CR in spark-ignition NG engines further.

Experimental investigation the effects of spark discharge characteristics on the heavy-duty spark ignition natural gas engine at low load condition

The fuel economy of natural gas (NG) spark ignition (SI) engine could improve significantly when using high exhaust gas recirculation (EGR) dilution. However, the combustion processes become instability and even occur misfire at higher EGR rate. In this paper, the high energy ignition system, which was the technology of variable spark, was utilized to extend the EGR tolerance of a SI engine. Extensive experimental tests were conducted to investigate the effects of spark discharge current and duration on combustion and emissions characteristics at low load condition. The results showed that the fuel economy was improved with the spark discharge energy at the high EGR rate of 30%. The increase amplitude of fuel economy was 1.32% when the spark discharge energy increased from 210 to 320 mJ. The effective spark discharge energy was existed in consideration of the fuel economy. The ignition delay (CA0-5) and the flame propagation period (CA10-90) shortened with an increase in spark discharge energy. Besides, NOx emissions were more sensitive to the spark discharge energy than that of HC and CO emissions. As the spark discharge energy increased, the increase extent of NOx emissions was 26.9%, while HC and CO emissions decrease slightly.

Effect of hydrogen enrichment on the flame propagation, emissions formation and energy balance of the natural gas spark ignition engine

Technically, using hydrogen in the natural gas (NG) will increase the combustion rate of the spark ignition (SI) engine, particularly at the lean burn condition, which also benefits to improve the thermal efficiency and combustion efficiency. The aim of this study was to investigate the effect of hydrogen addition on the flame propagation, emissions formation, energy balance and the relationships between exhaust emissions and mediate species during the flame propagation in the natural gas (NG) SI engine. The 1D and 3D simulation models of the NG SI engine were built and validated against with experimental data. The results indicated that the initial spark kernel volume of the NG SI engine with hydrogen addition was larger than that of without hydrogen enriched. The NO concentration increased with the hydrogen due to its higher peak combustion temperature. The NO emission mainly generated inside the flame front, where located in the high temperature combustion zone. In addition, the CO formation rate of the NG SI engine with the hydrogen addition was faster and oxidized more completely. With adding hydrogen in natural gas, the amount of H and OH were significantly increased due to the chemical amplifiers, thereby enhancing the radical pool. The HC and soot emissions of the NG SI engine were much lower with the hydrogen addition. Furthermore, the energy efficiency and fuel economy of the NG SI engine were improved with the hydrogen addition, particularly at the lean mixture conditions.

Investigation on mixture formation and combustion characteristics of a heavy-duty SI methanol engine

• A high-pressure PFI system is utilized on a heavy-duty methanol SI engine. • The mixture formation process and its homogeneity are studied theoretically. • The optimized injection strategy can improve the mixture homogeneity. • The optimized injection strategy can improve the engine brake thermal efficiency. Due to the simplicity of the exhaust gas aftertreatment system, the heavy-duty natural gas spark ignition (SI) engines play an important role in achieving the macro targets of the reduction of petroleum consumption, carbon and harmful emissions. Considering that power-to-methanol is economically more feasible than power-to-methane, methanol is proposed to continue the advantages of natural gas engines. Based on the fuel properties of methanol and our researching experience, methanol mixture preparation and flow within the cylinder are the most significant. A novel high-pressure port fuel injection (PFI) system is utilized to promote atomization and evaporation of methanol. The effects of the injection strategy, including injection pressure (p inj ) and injection timing (α inj ), and excess air–fuel ratio (λ) on the mixture formation were simulated and then studied by engine experiments. Three-dimensional simulation and engine tests were conducted under the condition of 1500 rpm and the brake mean effective pressure (BMEP) of 0.854 MPa. p inj varied from 8 MPa to 24 MPa by 4 MPa, α inj was from 240°CA BTDC to 400°CA BTDC by 40°CA and λ was set to be 1.1,1.2 and 1.3, respectively. Simulation results indicate that the mixture homogeneity can be promoted by the optimized injection strategy. The mixture is the most homogeneous at α inj = 340 °CA BTDC and p inj = 8 MPa and the most inhomogeneous at α inj = 400 °CA BTDC and p inj = 24 MPa when λ = 1.2. The experimental results indicate that the more homogeneous mixture can improve engine brake thermal efficiency by shortening CA 0-10 and CA 10-90 as well as methanol lean-burn. The optimized injection strategy can improve the brake thermal efficiency by 2.6%, 2.7% and 2.8% when λ = 1.1, 1.2 and 1.3, respectively.

Impacts of the horizontal swirl and axial tumble on the turbulent kinetic energy and combustion process of a natural gas engine

ABSTRACT Natural gas (NG) engines are restricted by slow combustion rates. An appropriate flow condition is considered to be the most promising way to improve the combustion rate of NG. In this study, decoupling analysis of the impacts of swirl and tumble on turbulent kinetic energy (TKE) and combustion process of a spark ignition (SI) NG engine was conducted by simulation. A 3D model was established and boundary conditions of the most economical operating point (1200 r/min, 100% load) were obtained through tests, and the rationality of the case was verified. Then, the flow field of the original engine was decoupled at the intake valve closing time to obtain the decoupled swirl field and the decoupled tumble field. Finally, the swirl field and the tumble field were amplified and applied to the SI NG engine. The results showed that high swirl or tumble can obtain high TKE, but the contribution mechanism of them to TKE is significantly different. According to the analysis of the spatial motion structure and energy conversion, the TKE in tumble field is much higher than that in swirl field with the same intensity. In addition, the impacts of swirl and tumble on the combustion process of the SI NG engine are both divided into two phases, and high swirl or tumble can obtain higher thermal efficiency. The combustion rate of NG first increased with the increase in initial flow field strength. When the swirl ratio at intake valve closing time (SR0) and the tumble ratio at intake valve closing time (TR0) exceeded 2.0 and 1.25, respectively, the combustion rate is kept in a fluctuating equilibrium state. At this time, the improvement of swirl and tumble on NG combustion process was brought into full play, the maximum indicated thermal efficiency reached 43.18% and 44.39%, respectively. Finally, the conclusion was drawn by comparing swirl and tumble in different aspects where high tumble shows greater potential in achieving super-high thermal efficiency.

Study of the Effect of Air Injection On the Surge and Flow Characteristic of Compressor and the Pumping Loss in a Heavy-Duty Turbocharged NGSI Engine

Abstract In this study, bench tests of a heavy-duty turbocharged natural gas spark ignition (NGSI) engine were conducted with intake air injection at full load and different engine speeds. The flow characteristic of the compressor was revealed. The flow capacity of the compressor is reduced with air injection, and the reduction range increases gradually with the air injection pressure increasing at a constant speed, which would likely lead the compressor to surge. But the decrease extent of the compressor flow rate is improved as the speed increases, which reduces the tendency of surge. Based on those, prediction models for safe air injection pressure which can avoid compressor surge during various operations were proposed and then validated with experimental data. In addition, the influence of air injection on the pumping loss was also analyzed. The turbocharger efficiency is reduced therefore the pumping loss of the engine is increased during the air injection process. At 1200 rpm, the pumping loss efficiency of the engine without air injection is 0.25%, while it is increased to 1.83% with an air injection pressure of 400kPa at the same load.

On the use of artificial neural networks to model the performance and emissions of a heavy-duty natural gas spark ignition engine

The use of computational models for internal combustion engine development is ubiquitous. Numerical simulations using simpler to complex physical models can predict engine’s performance and emissions, but they require large computational capabilities. By comparison, statistical methodologies are more economical tools in terms of time and resources. This paper investigated the use of an artificial neural network algorithm to simulate the nonlinear combustion process inside the cylinder. Three engine control variables (i.e. spark timing, mixture equivalence ratio, and engine speed) were set as the model inputs. Outputs included peak cylinder pressure and its location, maximum pressure rise rate, indicated mean effective pressure, ignition lag, combustion phasing, burn duration, exhaust temperature, and engine-out emissions (i.e. nitrogen oxides, carbon monoxide, and unburned hydrocarbons). Eighty percent of the experimental data from a heavy-duty natural gas spark ignition engine were utilized to train the model. The perceptions accurately learned the combustion characteristics and predicted engine responses with acceptable errors, evidenced by close-to-unity coefficient of determination and close-to-zero root-mean-square error. Moreover, the regressors captured the effect of key operating variables on the engine response, suggesting the well-trained models successfully identified the complex relationships and can help assist engine analysis. Overall, the neural network algorithm was appropriate for the application investigated in this study.

Machine learning assisted prediction of exhaust gas temperature of a heavy-duty natural gas spark ignition engine

Exhaust gas temperature is a key parameter for optimizing engine performance and emissions. Of particular interest is forecasting the exhaust gas temperature in a diesel engine converted to spark ignition natural gas operation, as the combustion process in this engine is significantly different from the one in a conventional engine. The goal was to assess four different machine learning algorithms namely the artificial neural network, random forest, support vector regression, and gradient boosting regression trees, with respect to a physical 1D CFD model and relative to one another, when predicting the exhaust temperature. The spark timing, equivalence ratio, and engine speed were model inputs. First, the artificial neural network predicted the exhaust temperature more accurately than the physical model, because of the complex premixed combustion phenomena inside a conventional diesel chamber. When compared relative to one another, all machine learning models predicted the exhaust gas temperature with acceptable error while also capturing its relationship with the three model inputs. The gradient boosting regression trees predicted the best, but it usually requires high quality noise-free data. The random forest had the least accuracy, but it required the least amount of calibration. The support vector regression had the smallest error, but it required the highest computational resources. The artificial neural network algorithm was the most appropriate, but it required effort in tuning its hyperparameters. Overall, the results showed that well-trained machine learning models can complement more complex physical model while also helping with optimizing the engine performance, emissions, and life.

A New Method to Determine the Impact of Individual Field Quantities on Cycle-to-Cycle Variations in a Spark-Ignited Gas Engine

Cycle-to-cycle variations (CCV) in spark-ignited (SI) engines impose performance limitations and in the extreme limit can lead to very strong, potentially damaging cycles. Thus, CCV force sub-optimal engine operating conditions. A deeper understanding of CCV is key to enabling control strategies, improving engine design and reducing the negative impact of CCV on engine operation. This paper presents a new simulation strategy which allows investigation of the impact of individual physical quantities (e.g., flow field or turbulence quantities) on CCV separately. As a first step, multi-cycle unsteady Reynolds-averaged Navier–Stokes (uRANS) computational fluid dynamics (CFD) simulations of a spark-ignited natural gas engine are performed. For each cycle, simulation results just prior to each spark timing are taken. Next, simulation results from different cycles are combined: one quantity, e.g., the flow field, is extracted from a snapshot of one given cycle, and all other quantities are taken from a snapshot from a different cycle. Such a combination yields a new snapshot. With the combined snapshot, the simulation is continued until the end of combustion. The results obtained with combined snapshots show that the velocity field seems to have the highest impact on CCV. Turbulence intensity, quantified by the turbulent kinetic energy and turbulent kinetic energy dissipation rate, has a similar value for all snapshots. Thus, their impact on CCV is small compared to the flow field. This novel methodology is very flexible and allows investigation of the sources of CCV which have been difficult to investigate in the past.

Numerical investigation of a fueled pre-chamber spark-ignition natural gas engine

Pre-chamber spark-ignition (PCSI) is a leading advanced ignition concept for internal combustion engines with the potential to enable diesel-like efficiency in medium-duty/heavy-duty (MD/HD) natural gas (NG) engines. By leveraging distributed ignition sources from multiple turbulent jets, the PCSI technology can deliver extremely short combustion duration in ultra-lean mixtures and significantly improve the engine thermal efficiency. However, in the automotive industry there is a lack of adequate science base and predictive simulation tools required for commercial development of PCSI engines. In this study, Reynolds-Average Navier-Stokes simulations are carried out to describe the combustion process in lean-burn NG engines, focusing on the combustion modeling approach. Two combustion models, multi-zone well-stirred reactor (MZ-WSR) and G-equation, are used to simulate the combustion process in an MD NG engine equipped with a fueled-PCSI system for four operating conditions close to the lean operating limit. A skeletal chemical mechanism and a laminar flame speed tabulation are used to compute the combustion accurately. Simulation results are compared with experimental data regarding measured cylinder pressure, heat release rate, and combustion duration. By dividing the PCSI combustion process into four distinct phases, the difference between the two models’ results for each phase is analyzed in detail. The MZ-WSR model overestimates the combustion duration for early flame kernel growth in the pre-chamber due to the lack of a specific formulation to take turbulence-chemistry interaction into account. Despite the prolonged combustion duration and low pressure built-up inside the pre-chamber, the model matches the combustion rate in the main-chamber. In contrast, the G-equation model delivers good agreements for the pre-chamber combustion and turbulent jet-driven combustion processes. However, the model starts to underestimate the combustion rate in the main-chamber, especially under ultra-lean mixture conditions. Finally, improvements are needed for both models to simulate the later combustion stage that occurred in the near-wall regions.