bluuebunny/crossref_metadata_2025_split huggingface dataset:
Engine Performance and Emissions for a Heavy-Duty Diesel Engine Converted to Stoichiometric Natural Gas Operation
Authors: Liu Jinlong , Ulishney Christopher , Dumitrescu Cosmin E. 
Published: December 2020

Abstract
Converting existing compression ignition (CI) engines to spark ignition (SI) operation can increase the use of natural gas (NG) in heavy-duty engine applications and reduce the reliance on petroleum fuels. Gas fumigation upstream of the intake manifold and the addition of a spark plug in place of the diesel injector to initiate and control the combustion process is a convenient approach for converting existing diesel engines to dedicated NG operation. Stoichiometric operation and a three-way catalytic converter can help the engine to comply with increasingly strict emission regulations. However, as the CI-to-SI conversion usually maintains the conventional geometry of a CI engine (i.e., maintains the flat cylinder head and the bowl-in piston), the goal of this study was to observe some of the effects that the diesel conversion to stoichiometric NG SI operation will have on the engine’s performance and emissions. Dynamometer tests were performed at a constant engine speed at 1300 rpm but various spark timings. The experimental results for a net indicated mean effective pressure ∼ 6.7 bar showed that ignition timing did not affect the end of combustion due to the slow-burn inside the squish. Moreover, the less-optimal conditions inside the squish led to increased carbon monoxide (CO) and unburned hydrocarbon (UHC) emissions. While the combustion event was stable with no signs of knocking at the medium load conditions investigated here, the results suggest that the engine control needs to optimize the mass fraction trapped inside the squish region for a higher efficiency and lower emissions.
Improving Machine Learning Model Performance in Predicting the Indicated Mean Effective Pressure of a Natural Gas Engine
Authors: Liu Jinlong , Ulishney Christopher , Dumitrescu Cosmin E. 
Published: December 2020

Abstract
Converting existing compression ignition engines to spark ignition approach is a promising approach to increase the application of natural gas in the heavy-duty transportation sector. However, the diesel-like environment dramatically affects the engine performance and emissions. As a result, experimental tests are needed to investigate the characteristics of such converted engines. A machine learning model based on bagged decision trees algorithm was established in this study to reduce the experimental cost and identify the operating conditions of special interest for analysis. Preliminary engine tests that changed spark timing, mixture equivalence ratio, and engine speed (three key engine operation variables) but maintained intake and boundary conditions were applied as model input to train such a correlative model. The model output was the indicated mean effective pressure, which is an engine parameter generally used to assist in locating high engine efficiency regions at constant engine speed and fuel/air ratio. After training, the correlative model can provide acceptable prediction performance except few outliers. Subsequently, boosting ensemble learning approach was applied in this study to help improve the model performance. Furthermore, the results showed that the boosted decision trees algorithm better described the combustion process inside the cylinder, as least for the operating conditions investigated in this study.
Optimization of Direct Water Injection Parameters to Improve the Trade-off Between Efficiency and NOx Emissions for a Lean-Burn CHP NG Engine
Authors: Beltaifa Youssef , Holzberger Sascha , Aslan Ferhat , Kettner Maurice , Eilts Peter 
Published: December 2020

Abstract
In the medium and long term, cogeneration plants in Germany will play an important role in the transition towards a cleaner and more efficient electricity and heat generation, compared to the conventional uncoupled power plants. For most of the currently used CHP (Combined Heat and Power) units, which operate with a lean-burn process, the NOx emissions limit represents an obstacle to increasing the electrical efficiency. Therefore, the lean burn process has become less attractive because of stricter future NOx emissions limit. In this context, the stoichiometric combustion process with a three-way catalytic converter provides a solution. However, the present study shows that lean burn operation still has potential due to direct water injection into the combustion chamber.
This work includes an experimental investigation of the impact of different injection parameters (beginning of injection timing, injection pressure difference and water-to-fuel ratio) on the effectiveness of direct water injection regarding the improvement of the trade-off between engine efficiency and NOx emissions. For the execution of the experimental investigations, a series-production CHP-engine was equipped with a direct injection system consisting of a high-pressure unit, a high-pressure pipe and a GDI-injector. For the injector integration, the cylinder head was machined sidewise (close to the exhaust gas valve). Furthermore, 3D CFD simulations of the injection process allowed gaining a deeper insight into the complex spray-flow interaction, wall film formation and evaporation at different injection timings. For the 3D CFD simulations, the spray model used was tuned with help of spray pictures, taken on the spray test bed.
Water injection at the beginning of the intake stroke (330 °CA BFTDC) reduces NOx emissions most effectively. Moreover, it causes the least engine efficiency loss. The increase of the injection pressure difference (between 20 and 80 bar) leads to a significant increase of the engine efficiency. However, it has a secondary effect on the NOx emissions reduction. The lowest NOx emissions are reached with an injection pressure difference of 60 bar. The combination of direct water injection (at the beginning of the intake stroke, injection pressure difference of 60 bar) with earlier combustion phasings enables an increase in the engine efficiency and a simultaneous decrease in NOx emissions without loss in engine performance. Main drawbacks of water injection are longer combustion duration and higher CO and HC emissions. In addition, the lower exhaust gas temperature causes a deterioration of the conversion of the HC molecules in the oxidation catalyst and reduces the heat recovery efficiency of the CHP-system.
X-Ray Characterization of Real Fuel Sprays for Gasoline Direct Injection
Authors: Sforzo Brandon A. , Tekawade Aniket , Kastengren Alan L. , Fezzaa Kamel , Ilavsky Jan , Powell Christopher F. , Pei Yuanjiang , Zhang Anqi , Levy Robert 
Published: December 2020

Abstract
The effects of fuel blend properties on spray and injector performance has been investigated for several operating conditions in a side-mount injector for Gasoline Direct Injection (GDI) using two certification fuel blends, Euro 5 and Euro 6. Several X-ray diagnostic techniques were conducted to characterize the injector and spray morphology. Detailed internal geometry of the GDI injector was measured with a feature-resolution of 1.8 micrometers, through the use of hard X-ray tomography. The geometry characterization of this six-hole GDI, side mount injector, quantifies relevant hole and counterbore dimensions and reveals the intricate details within the flow passages, including surface roughness and micron-sized features. Internal valve motion was measured with a temporal resolution of 20 microseconds and a spatial resolution of 2.0 micrometers, for three injection pressures and several injector energizing strategies. The needle motion for both fuels exhibit similar lift profiles for common energizing commands. A combination of X-ray radiography and Ultra-Small-Angle X-ray Scattering (USAXS) was used to characterize the fuel mass distribution and the droplet sizing, respectively. Tomographic spray radiography revealed the near-nozzle distribution of fuel mass for each of the fuels, and the asymmetry produced by the angled nozzles. Under evaporative conditions, the two fuels show minor differences in peak fuel mass distribution during steady injection, though both exhibit fluctuations in injection during the early, transient phase. US-AXS measurements of the path-specific surface area of the spray indicated lower peak values for the more evaporative conditions in the near nozzle region. These spray measurements portray the specific behavior of real fuel blends under a variety of conditions, illustrating the need to examine multi-component fuels to better understand relevant cases. Furthermore, this work furnishes the realistic boundary values for simulations to appropriately predict the sprays which were experimentally measured, and influenced by those realistic conditions.
An Automated Machine Learning-Genetic Algorithm (AutoML-GA) Framework With Active Learning for Design Optimization
Authors: Owoyele Opeoluwa , Pal Pinaki , Vidal Torreira Alvaro 
Published: December 2020

Abstract
The use of machine learning (ML) based surrogate models is a promising technique to significantly accelerate simulation-based design optimization of IC engines, due to the high computational cost of running computational fluid dynamics (CFD) simulations. However, surrogate-based optimization for IC engine applications suffers from two main issues. First, training ML models requires hyperparameter selection, often involving trial-and-error combined with domain expertise. The second issue is that the data required to train these models is often unknown a priori. In this work, we present an automated hyperparameter selection technique coupled with an active learning approach to address these challenges. The technique presented in this study involves the use of a Bayesian approach to optimize the hyperparameters of the base learners that make up a Super Learner model to obtain better test performance. In addition to performing hyperparameter optimization (HPO), an active learning approach is employed, where the process of data generation using simulations, ML training, and surrogate optimization, is performed repeatedly to refine the solution in the vicinity of the predicted optimum. The proposed approach is applied to the optimization of a compression ignition engine with control parameters relating to fuel injection, in-cylinder flow, and thermodynamic conditions. It is demonstrated that by automatically selecting the best values of the hyperparameters, a 1.6% improvement in merit value is obtained, compared to an improvement of 1.0% with default hyperparameters. Overall, the framework introduced in this study reduces the need for technical expertise in training ML models for optimization, while also reducing the number of simulations needed for performing surrogate-based design optimization.
RCCI With High Reactivity S8-ULSD Blend and Low Reactivity N-Butanol
Authors: Soloiu Valentin , Carapia Cesar E. , Smith Richard , Weaver Amanda , Mckinney Levi , Mothershed David , Grall Drake , Ilie Marcel , Rahman Mosfequr 
Published: December 2020

Abstract
A fuel blend consisting of 10% S8 by mass (a Fischer-Tropsch synthetic kerosene), and 90% ULSD (Ultra Low Sulfur Diesel) was investigated for their combustion characteristics and impact on emissions during RCCI (Reactivity Controlled Compression Ignition) combustion in a single cylinder experimental engine utilizing a 65% by mass n-butanol port fuel injection (PFI). RCCI is a dual fuel combustion strategy achieved with the introduction of a PFI fuel of the low-reactive n-butanol, and a direct injection (DI) of a high-reactivity blend (FT-BLEND) into an experimental diesel engine. The combustion analysis and emissions testing were conducted at 1500 RPM at an engine load of 5 bar IMEP (Indicated Mean Effective Pressure), and CA50 of 9° ATDC (After Top Dead Center); CDC (Conventional Diesel Combustion) and RCCI with 65Bu-35ULSD were utilized as the baseline for AHRR (Apparent Heat Release Rate), ringing and emissions comparisons. It was found during a preliminary investigation with a Constant Volume Combustion Chamber (CVCC) that the introduction of 10% by mass S8 into a mixture with 90% ULSD by mass only increased Derived Cetane Number (DCN) by 0.8, yet it was found to have a significant effect on the combustion characteristics of the fuel blend.
This led to the change in injection timing necessary for maintaining 65Bu-35F-T BLEND RCCI at a CA50 of 5° ATDC (After Top Dead Center) to be shifted 3° closer to TDC, thus affecting the Ringing Intensity (RI), Pressure Rise Rate, and heat release of the blend all to decrease. CDC was conducted with a primary injection of 14° BTDC at a rail pressure of 800 bar, all RCCI testing was conducted with 65% PFI of n-butanol by mass and 35% DI, to prevent knock, with a rail pressure of 600 bar and a pilot injection of 60° BTDC for 0.35 ms. 65Bu-35ULSD RCCI was conducted with a primary injection at 6° BTDC with neat ULSD#2, the fuel 65Bu-35F-T BLEND in RCCI had a primary injection at 3° BTDC to maintain CA50 at 9° ATDC. 65Bu-35ULSD RCCI experienced a NOx and soot emissions decrease of 40.8% and 91.44% respectively in comparison to CDC. The fuel 65Bu-35F-T BLEND in RCCI exhibited an additional decrease of NOx and soot of 32.9 and 5.3%, in comparison to 65Bu-35ULSD RCCI for an overall decrease in emissions of 73.7% and 96.71% respectively. Ringing Intensity followed a similar trend with reductions in RI for 65Bu-35ULSD RCCI decreasing only by 6.2% whereas 65Bu-35F-T BLEND had a decrease in RI of 76.6%. Although emissions for both RCCI fuels experienced a decrease in NOx and soot in comparison to CDC, UHC and CO did increase as a result of RCCI. CO emissions for 65Bu-35ULSD RCCI and 65Bu-35F-T BLEND where increased from CDC by a factor of 5 and 4 respectively with UHC emissions rising from CDC by a factor of 3.4. The fuel 65Bu-35F-T BLEND had a higher combustion efficiency than 65Bu-35ULSD in RCCI at 91.2% due to lower CO emissions of the blend.
Comparing Cetane Number Measurement Methods
Authors: Abel Riley C. , Luecke Jon , Ratcliff Matthew A. , Zigler Bradley T. 
Published: December 2020

Abstract
Cetane number is one of the most important fuel performance metrics for mixing controlled compression-ignition “diesel” engines, quantifying a fuel’s propensity for autoignition when injected into end-of-compression-type temperature and pressure conditions. The historical default and referee method on a Cooperative Fuel Research (CFR) engine configured with indirect fuel injection and variable compression ratio is cetane number (CN) rating. A subject fuel is evaluated against primary reference fuel blends, with heptamethylnonane defining a low-reactivity endpoint of CN = 15 and hexadecane defining a high-reactivity endpoint of CN = 100. While the CN scale covers the range from zero (0) to 100, typical testing is in the range of 30 to 65 CN. Alternatively, several constant-volume combustion chamber (CVCC)-based cetane rating devices have been developed to rate fuels with an equivalent derived cetane number (DCN) or indicated cetane number (ICN). These devices measure ignition delay for fuel injected into a fixed volume of high-temperature and high-pressure air to simulate end-of-compression-type conditions. In this study, a range of novel fuel compounds are evaluated across three CVCC methods: the Ignition Quality Tester (IQT), Fuel Ignition Tester (FIT), and Advanced Fuel Ignition Delay Analyzer (AFIDA). Resulting DCNs and ICNs are compared for fuels within the normal diesel fuel range of reactivity, as well as very high (∼100) and very low DCNs/ICNs (∼5). Distinct differences between results from various devices are discussed. This is important to consider because some new, high-efficiency advanced compression-ignition (CI) engine combustion strategies operate with more kinetically controlled distributed combustion as opposed to mixing controlled diffusion flames. These advanced combustion strategies may benefit from new fuel chemistries, but current rating methods of CN, DCN, and ICN may not fully describe their performance. In addition, recent evidence suggests ignition delay in modern on-road diesel engines with high-pressure common rail fuel injection systems may no longer directly correlate to traditional CN fuel ratings. Simulated end-of-compression conditions are compared for CN, DCN, and ICN and discussed in the context of modern diesel engines to provide additional insight. Results highlight the potential need for revised and/or multiple fuel test conditions to measure fuel performance for advanced CI strategies.
Study on Design Method of Combustion Reference Values for Model-Based Control of Advanced Diesel Engine
Authors: Kim Jihoon , Yamasaki Yudai 
Published: December 2020

Abstract
Model-based control systems are drawing attention in relation to implementing next-generation combustion technologies with high thermal efficiency and low emissions, such as homogeneous charge compression ignition (HCCI) and premixed charge compression ignition (PCCI) combustion, which have low robustness. A model-based control system derives control inputs according to reference values and operating conditions during every cycle and has potential to replace the conventional control map, which requires a large number of experiments. However, model-based control for engines requires reference values for combustion, such as heat release peak timing and heat release peak value; such values represent the combustion state. Therefore, the reference for the transient condition is important for utilizing the benefit of model-based control systems, given that such systems derive control outputs cycle by cycle.
In this study, a design method for the combustion reference values for the transient operating condition is described for advanced diesel combustion, which uses premixed compression ignition combustion by multiple fuel injections. Specifically, a statistical method and a method based on model prediction considering the driving characteristics are proposed and compared in engine control experiments. These proposed methods were evaluated under defined simple transient operation conditions and worldwide harmonized light vehicles test cycles (WLTC) mode considering real road conditions. Results showed that designing the combustion reference values for transient operation by model prediction is effective, and such method has the potential to reflect the driving characteristics.
Influence of Fuel Properties on GDI PM Emissions Over First 200 Seconds of WLTP Using an Engine Dynamometer and Novel “Virtual Drivetrain” Software
Authors: Bock Noah R. , Northrop William F. 
Published: December 2020

Abstract
The influence of fuel properties on particulate matter (PM) emissions from a catalytic gasoline particulate filter (GPF) equipped gasoline direct injection (GDI) engine were investigated using novel “virtual drivetrain” software and an engine mated to an engine dynamometer. The virtual drivetrain software was developed in LabVIEW to operate the engine on an engine dynamometer as if it were in a vehicle undergoing a driving cycle. The software uses a physics-based approach to determine vehicle acceleration and speed based on engine load and a programed “shift” schedule to control engine speed. The software uses a control algorithm to modulate engine load and braking to match a calculated vehicle speed with the prescribed speed trace of the driving cycle of choice. The first 200 seconds of the WLTP driving cycle was tested using 6 different fuel formulations of varying volatility, aromaticity, and ethanol concentration. The first 200 seconds of the WLTP was chosen as the test condition because it is the most problematic section of the driving cycle for controlling PM emissions due to the cold start and cold drive-off. It was found that there was a strong correlation between aromaticity of the fuel and the engine-out PM emissions, with the highest emitting fuel producing more than double the mass emissions of the low PM production fuel. However, the post-GPF PM emissions depended greatly on the soot loading state of the GPF. The fuel with the highest engine-out PM emissions produced comparable post-GPF emissions to the lowest PM producing fuel over the driving cycle when the GPF was loaded over three cycles with the respective fuels. These results demonstrate the importance of GPF loading state when aftertreatment systems are used for PM reduction. It also shows that GPF control may be more important than fuel properties, and that regulatory compliance for PM can be achieved with proper GPF control calibration irrespective of fuel type.
Fuel and Engine Management System for Gaseous-Fueled Spark-Ignition Non-Road Engines
Authors: Sherwin Daniel , Dees Jesse 
Published: December 2020

Abstract
A fuel and engine management system have been successively applied to a 4.5L spark-ignition gaseous-fueled engine used for stationary power generation applications up to 80 kW. The system operates on low-pressure commercial grade natural gas or liquid propane gas and governs engine speed at either 1500 or 1800 rpm, for generator frequencies of 50 Hz and 60 Hz respectively. The fuel and engine management system consist of an engine control module, an electronically controlled fuel mixer, a fuel pressure sensor, and other supporting sensors/actuators. This new system replaces a legacy of fixed-orifice metering or vacuum-actuated-valve mechanical mixer designs. This new system allows for closed-loop control of stoichiometric combustion that meets both performance and emissions requirements without the need for a fuel pressure regulator within the genset frame. It also allows a single fuel system assembly to be used on all 4.5L engines regardless of fuel type (LP/NG) or nominal speed (50/60Hz), as these are now selected with standard J1939 CAN protocol messages from the genset controller. This paper reviews the development aspects for the new fuel system on the 4.5L engine.
The electronic-actuated fuel mixer system offers a wider range of fuel flow control compared to mechanical-actuated mixers, this results in better air-fuel control due to variations in fuel quality, low fuel supply pressure and changing ambient conditions. The range of fuel control is result of the different mixer valve construction and control. The fuel metering valve is a butterfly type and is controlled from a stepper motor. The valve controls the fuel flow rate just before the fuel mixes with the combustion air passing thought a venturi. Lag in fuel flow, typical of low supply pressure and low restriction / signal venturi, is corrected for using a feedforward control strategy based on genset electrical load. The mixer sizing and flow bench measurements for calibration, will be reviewed.
The ECM uses a speed-density air flow model, along with fuel supply and air filter pressure, to determine the best mixer valve position. The engine air flow model is used for determining venturi flow and the resulting mixer vacuum signal, but a final calibration correction was created with hot wire-anemometer-flow meters on a running engine. A long-term fuel trim is also applied to the mixer position, but unlike a fuel-injection system which corrects volumetric efficiency based on known fuel flow rate and HEGO sensor feedback, this mixer control strategy learns a steady-state mixer correction or offset. The entire control strategy was developed within a Simulink model and auto code generation tools were used to create final ECM C and machine code. The development of the mixer and ECM control strategy will be detailed herein.