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At least 37 records · Page 2

CFD modeling of pre-spark heat release in a boosted direct-injection spark-ignition engine

Accurate predictions of low-temperature heat release (LTHR) are critical for modeling auto-ignition processes in internal combustion engines. While LTHR is typically obscured by deflagration, extremely late ignition phasing can lead to LTHR prior to the spark, a behavior known as pre-spark heat release (PSHR). In this research, PSHR in a boosted direct-injection spark-ignition engine was studied using 3-D computational fluid dynamics (CFD) and detailed chemical kinetics. The turbulent combustion was modeled via a hybrid approach that incorporates the G-equation model for tracking the turbulent flame front, and the well-stirred reactor model with detailed chemistry for assessing the low-temperature reactions in unburnt gas. Simulations were conducted using Co-Optima alkylate and E30 fuels at operating conditions characterized by different PSHR intensities. The predicted in-cylinder pressure and heat release rate were found to agree well with experiments. It was found the estimate of previous-cycle trapped residuals is of utmost importance for capturing PSHR correctly. A simulation best practice was developed which keeps the detailed chemistry solver active throughout the entire simulation, allowing to track the evolution of intermediate species from one cycle to the next. Following the validation, the dynamics of PSHR were analyzed in detail employing the pressure-temperature (P-T) trajectory framework. It was shown that PSHR correlated with the first-stage ignition delay of the fuel, hence showing close relation to the in-cylinder P-T trajectory and the chemical kinetics. Besides, it was indicated that LTHR is a self-limiting process that has the effect of attenuating the thermal stratification in the combustion chamber. Furthermore, it was observed the occurrence of PSHR caused the P-T trajectory of end-gas to overlap with the negative temperature coefficient region of the fuel’s ignition-delay maps. This effect was more significant in the fuel-rich regions where engine knock tendency would be generally higher, with potential implications on knock control and mitigation.

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Physically-based control-oriented modeling for turbocharged stoichiometric spark-ignited engine with cooled EGR and flexible VVT systems

Accurate estimation and prediction of engine gas exchange system and in-cylinder conditions are critical for spark-ignited engine control and diagnostic algorithm development. In this paper, a physically-based, control-oriented model for a 2.8 l turbocharged, variable valve timing (VVT) and low pressure (LP) exhaust gas recirculation (EGR)-utilizing SI engine was developed. The model includes the impact of modulation to any combination of 10 actuators, including the throttle valve, compressor bypass valve, fueling rate, waste-gate, LP EGR valve, number of deactivated cylinders, intake valve open (IVO) timing, intake valve close (IVC) timing, exhaust valve open (EVO) timing and exhaust valve close (EVC) timing. The accuracy of the model in capturing engine dynamics was demonstrated by validating it against high-fidelity engine GT-Power simulation results for various drive cycles, particularly emphasizing elevated loads. In comparison to the open literature, novel contributions of the effort described in this paper includes in-cylinder gas composition modeling and turbine-out pressure estimation.

Zhang, Xu↗

Experimental Investigation of Gaseous Mixtures of Ethane, Methane, and Carbon Dioxide as an Alternative to Conventional Fuel in Spark Ignition Engines

This study investigates the viability and performance of certain synthetic fuels in spark ignition internal combustion engine based stationary power generation wherein the fuel comprises a mixture of methane and ethane in high dilutions of carbon dioxide (CO 2 ). The fuel of concern is a byproduct of a novel method for producing ethylene from ethane. The byproduct gas mixture has a concentration of approximately 41% CO 2 , 40% ethane, and 5% methane by weight along with other minor compounds. Varying mixtures of ethane and methane combined with between 42% and 46% by weight CO 2 were used to evaluate the viability and efficiency of this fuel to operate in existing internal combustion engines as a means of reducing emissions and increasing industrial process efficiency. A 13 hp gasoline generator was repurposed as a test stand by incorporating a modified fuel induction system and instrumentation for data collection. A gas metering and mixing system was installed to precisely control the mass flow of gases induced into the engine. Various instrumentations were installed to monitor in-cylinder pressure, temperature at various locations, emissions, and fuel and airflow rates. Varying fuel mixtures and loads were tested and compared to gasoline. It was found that under a high load, the mixed gas was able to generate comparable thermal efficiency and power to gasoline. But under no load or a part load condition the indicated thermal efficiency was found to be about 21% lower than that of gasoline. Further, the mixed gas also resulted in up to 50% reduction in CO and NOx emissions when compared to gasoline.

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Ability of Particulate Matter Index to describe sooting tendency of various gasoline formulations in a stratified-charge spark-ignition engine

This study investigates the ability of Particulate Matter Index (PMI) to describe the sooting behavior of various gasoline formulations in a stratified-charge (SC) spark-ignition engine. Specifically, the engine was operated at 2000 rpm with an intake pressure of 130 kPa where soot formation is known to primarily occur in the bulk gases. Exhaust soot emissions were measured for nine test fuels at various exhaust gas recirculation levels. A comparison between measured soot levels and PMI shows that PMI is a relatively poor predictor of the sooting tendency of the tested fuels under lean SC combustion. Among the fuels, three fuels, namely the diisobutylene blend, High Olefin, and E30 fuels exhibit measured soot behavior opposite of that predicted by PMI. Optical diagnostics were utilized to further investigate the in-cylinder phenomena for these three fuels. Analysis of natural luminosity and diffused back-illumination extinction imaging suggests that fuel-induced differences in the amount of soot formed are responsible for a majority of the discrepancy in measured versus predicted sooting tendency. Fuel-induced differences in soot oxidation and spray development seem to play minor roles. Because the combustion and air-fuel mixing processes for lean SC combustion are different from conventional stoichiometric operation it is hypothesized that the PMI correlation needs to be modified to account for differences in stoichiometric air-fuel ratio and level of oxygenation between fuels. Furthermore, the role of fuel volatility in PMI possibly needs to be de-emphasized for SC operation with fuel injection into compression-heated gases.

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Effects of blending C3-C4 alcohols on motor gasoline properties and performance of spark ignition engines: A review

Supplementing petroleum fuels with sustainable and renewable alternatives is a good option for increasing the sustainability of transportation fuels. Alcohols are particularly attractive blendstocks for spark ignition engines, mainly due to their desirable fuel properties including high octane, evaporative cooling, and reduced sooting propensity. Although the use of SI engines is widespread around the world, predominately for light duty vehicles, concerns about CO2 emissions and other sustainability issues necessitate increased engine efficiencies, reduced tailpipe pollutants, and lower lifecycle carbon emissions. The intelligent blending of C2-C4 alcohols into motor gasoline is a viable method for achieving these goals. There are a multitude of ways to produce renewable alcohols such as through fermentation from first-generation feedstocks (sugar and corn) and second-generation feedstocks (lignocellulosic biomass), or by gasification and mixed alcohol fuel synthesis routes from lignocellulosic biomass. Currently ethanol is extensively used in motor gasoline fuels worldwide and although many have proposed the use of C3 and C4 alcohols in motor gasoline as an improvement over ethanol, the higher cost of production and lack of clear definition as to their benefit over ethanol when blended into motor gasoline have led to slow acceptance into the market. In this review, special emphasis is placed on the effects of blending C3 and C4 alcohols into motor gasoline in terms of physicochemical properties, volatility behavior, and engine performance when compared to ethanol blends. Furthermore, the impact of blending C3 and C4 alcohols with gasoline on emission (particulate matter, nitrogen oxides, carbon monoxide, hydrocarbons, and unregulated oxygenates) and combustion (volumetric efficiency, thermal efficiency, fuel consumption, and cold performance) characteristics is discussed. Although there are some disagreements in the literature over the effect of alcohols predominately around the type of SI engine, i.e., port fuel injected versus direct fuel injected and engine operating mode, generally it is stated that alcohols can potentially reduce soot, unburned hydrocarbons and CO emissions while increasing thermal efficiency when proper engine configuration/calibration is used. Lastly, research that must be conducted to find the optimum combination of alcohol blends and engine configurations is highlighted and discussed.

09 BIOMASS FUELS↗

Shock tube investigation of high-temperature, extremely-rich oxidation of several co-optima biofuels for spark-ignition engines

To reduce the reliance on fossil fuels in the transportation sector and increase combustion efficiency, the Co-Optima initiative from US Department of Energy identified the top 10 biofuels for downsized, boosted, spark-ignition engines. Most of these biofuels have detailed reaction mechanisms available in literature developed based on studies at temperatures lower than 1700 K and an equivalence ratio of less than five. As such, the performance of these detailed mechanisms at high temperature and extremely rich conditions are unknown. It is important to validate kinetic mechanisms at these conditions because they are conducive to soot formation. Prediction of soot by chemical kinetic models relies on the prediction of underlying benchmark species like carbon monoxide and ethylene. In this work, we conduct high temperature (1700–2050 K) and high equivalence ratio(Φ=8.6) oxidation of these biofuels, namely 2,4,4-trimethyl-1-pentene (α-diisobutylene), ethanol, cyclopentanone, methyl acetate, and 2-methylfuran, blended in ethylene behind reflected shock waves at 4–4.7 atm pressure. Carbon monoxide and ethylene time histories are measured simultaneously using a continuous feedback quantum cascade laser near 4.9 µm and a tunable CO 2 gas laser at 10.532 nm, respectively. Results show that ethanol blend forms more carbon monoxide than other biofuels and consumes ethylene faster than the biofuel blends in the temperature range considered. Overall, the performance of different mechanisms in literature are evaluated against the experimental results. The novel reaction mechanism ‘the Co-Optima model’, which includes the sub mechanisms for all the biofuels in this study, was found to be the best mechanism for the experimental conditions studied.

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Advanced Light-Duty Spark Ignition Engine Research: Co-Optimization of Fuels and Engines and Partnership to Advance Combustion Engines (FY2020 Annual Progress Report)

This report covers recent progress on research tasks that support both the Co-Optimization of Fuels and Engines (Co-Optima) initiative and the Partnership to Advance Combustion Engines (PACE) consortium. The Co-Optima tasks further the science-base needed by industry stakeholders to co-evolve the next generation of highly efficient direct injection spark ignition (DISI) engines and new gasoline-type fuels. The research emphasis is on fuel effects on multimode spark ignition (SI) engine operation, which uses traditional non-dilute stoichiometric operation for peak load and power but reverts to lean operation at lower loads to provide higher fuel economy. This work focuses on determining desirable fuel specifications in terms of well-established metrics like research octane number (RON) and motor octane number, but it also involves the assessment of new fuel metrics, including fuel sooting propensity and phi-sensitivity. The PACE task supports the development of predictive computational fluid dynamics (CFD) modeling, which promises to unlock new strategies for high-efficiency combustion while minimizing tailpipe emissions. Here, the primary fuel is a regular E10 gasoline (i.e., a regular gasoline blend containing 10% ethanol), and focus is on fuel-spray dynamics and soot emissions. Soot-formation pathways are studied to determine how the pathways change with injection strategies and the thermal state of the engine (i.e., cold-starting vs. fully warmed-up operation). This PACE task also contributed to the development of an optimal E10 gasoline surrogate fuel, as reported in detail elsewhere

33 ADVANCED PROPULSION SYSTEMS↗

Octane Requirements of Lean Mixed-Mode Combustion in a Direct-Injection Spark-Ignition Engine

Here, this study investigates the octane requirements of a hybrid flame propagation and controlled autoignition mode referred to as mixed-mode combustion (MMC), which allows for strong control over combustion parameters via a spark-initiated deflagration phase. Due to the throughput limitations associated with both experiments and 3-D computational fluid dynamics calculations, a hybrid 0-D and 1-D modeling methodology was developed, supported by experimental validation data. This modeling approach relied on 1-D, two-zone engine simulations to predict bulk in-cylinder thermodynamic conditions over a range of engine speeds, compression ratios, intake pressures, trapped residual levels, fueling rates, and spark timings. Those predictions were then transferred to a 0-D chemical kinetic model, which was used to evaluate the autoignition behavior of fuels when subjected to temperature–pressure trajectories of interest. Finally, the predicted autoignition phasings were screened relative to the progress of the modeled deflagration-based combustion in order to determine if an operating condition was feasible or infeasible due to knock or stability limits. The combined modeling and experimental results reveal that MMC has an octane requirement similar to modern stoichiometric spark-ignition engines in that fuels with high research octane number (RON) and high octane sensitivity (S) enable higher loads. Experimental trends with varying RON and S were well predicted by the model for 1000 and 1400 rpm, confirming its utility in identifying the compatibility of a fuel’s autoignition behavior with an engine configuration and operating strategy. However, the model was not effective in predicting (nor designed to predict) operability limits due to cycle-to-cycle variations, which experimentally inhibited operation of some fuels at 2000 rpm. Putting the operable limits and efficiency from MMC in the context of a state-of-the-art engine, the MMC showed superior efficiencies over the range investigated, demonstrating the potential to further improve fuel economy.

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Hybrid combustion modeling approach for turbulent jet ignition in natural-gas pre-chamber spark-ignition engines at high EGR

Here, this study presented a hybrid modeling approach for simulating turbulent jet ignition and combustion processes in a natural-gas pre-chamber spark-ignition engine operating under exhaust gas recirculation (EGR) diluted conditions. In-depth analyses of experimental data and simulation results from previous work [Chinnathambi et al., ICEF2021-67836; Kim et al., Fuel 409: 137815, 2026] revealed two key findings: (i) the magnitude of pressure difference between the pre-chamber and main chamber ($∆P_{PC-MC}$) was positively correlated with the combustion duration from the moment of $∆P_{PC-MC}=0$ to the point of 5% mass fraction burned, with larger $∆P_{PC-MC}$ associated with longer duration; and (ii) the turbulent combustion regime in the main chamber transitioned from the broken reaction zone to the corrugated flamelet regime, with the Karlovitz number exceeding 100 immediately after turbulent hot jets were ejected from nozzles, coinciding with observed local extinction events. To accurately simulate the entire combustion process, a hybrid approach was developed under Reynolds-Averaged Navier Stokes framework, combining the G-equation model for pre-chamber combustion with the multi-zone well-stirred reactor approach and a turbulence-chemistry interaction (TCI) submodel for main chamber combustion. The TCI submodel accounted for the attenuation of reaction rates due to turbulent strain and modeled local extinction by suppressing reaction rates under certain flow and flame conditions. When applied to three EGR rate conditions toward the dilution limit, the hybrid modeling approach accurately reproduced experimental data in terms of cylinder pressure, apparent heat release rate, and the observed positive correlation, including the delayed onset of main chamber combustion—a feature not captured by existing combustion models.

computational fluid dynamics simulation↗

A detailed experimental and modeling comparison of molecular radiative heat loss in a spark-ignition engine

Radiative heat transfer has been chiefly considered negligible in internal combustion engines, except for Diesel engines where soot radiation was recognized as a significant radiative transfer source. Only more recently, detailed simulations have shown that molecular radiation can be substantial as well. In extension to this, molecular radiative heat transfer can reach detectable levels of about 5–10% of the total heat transfer in spark-ignited engines. The broadband radiative nature of the significant emitting molecules, carbon dioxide and water, makes it necessary to address whether radiative trapping plays a substantial role in either total heat loss or energy redistribution within the cylinder. An experimental setup that allows measurements of the infrared emissions at a 2-crank-angle-degree resolution was developed to determine the importance of radiative trapping by carbon dioxide and water. Measurements were conducted in the well-characterized and documented TCC-III engine at the University of Michigan. The engine operated on a stoichiometric propane/air mixture at a speed of 1,300 RPM. Large Eddy Simulations with added line-by-line photon Monte-Carlo simulations of the molecular radiation were an integral part of this study to plan and devise the measurements. Post-processing of the simulation data included an accurate representation of the experimental volume from where infrared signals are collected. Additionally, the experimental data were used for validation of the photon Monte-Carlo simulations. Joint analysis of experimental and simulated spectra allowed quantifying the significance of radiative trapping. Results show the significant role of radiative trapping when predicting radiative heat transfer in the TCC-III engine.

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Large-eddy simulation study on cycle-to-cycle variation of knocking combustion in a spark-ignition engine

The cycle-to-cycle variation in the knock intensity is commonly encountered under abnormal combustion conditions. The severity of these abnormal combustion events can vary significantly, and the efficiency of engines at high loads is limited in practice by heavy knocking phenomena. Since, a thorough analysis of such recurrent but non-cyclic phenomena via experiments alone becomes highly cumbersome, in the present work, a multi-cycle large-eddy simulation study was performed to quantitatively predict cyclic variability in the combustion process and cyclic knock intensity variability in a direct injection spark-ignition engine. To account for the turbulence-chemistry interaction effects on flame propagation, the G-equation combustion model was used. Detailed chemistry was solved outside the flame front with a toluene primary reference fuel skeletal kinetic mechanism. For both the mild knock and heavy knock conditions, the numerical results were validated against experimental measurements. Based on the simulation results, a correlation analysis was performed considering combustion phasing, peak cylinder pressure and maximum amplitude of pressure oscillation. Furthermore, a detailed three-dimensional spatial analysis illustrated the evolution of auto-ignition kernel development and propagation of pressure waves during knocking combustion for three typical cycles with different knock intensities. In this process, it was found that an early occurrence of auto-ignition in the end gas was prone to high knock intensity. Although multiple auto-ignition kernels were observed in different cycles, the degree of coupling between chemical heat release and pressure waves varied, thereby leading to different maximum amplitude of pressure oscillation values.

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Artificial-intelligence-based prediction and control of combustion instabilities in spark-ignition engines

In recent years, as engine control strategies have grown increasingly sophisticated in a continued drive for increasing efficiency and reducing emissions, engine operation has been pushed into regimes that are limited by combustion instabilities. These instabilities produce undesirable abnormal combustion events, which pose barriers to further improvement in engine efficiency. Many of the phenomena involved are difficult to model or control using traditional, purely physics-based models and reactive control approaches. Artificial intelligence (AI) techniques offer some promise for achieving more effective combustion stability control, especially when appropriately applied within a physics-informed framework. This chapter illustrates the current state-of-the-art in applying AI to combustion stability control and examines three case studies with application to the dilute stability limit in spark-ignition engines to illustrate the utility and limitations of AI in these applications.

Maldonado Puente, Bryan↗

Large Eddy Simulation of Lean Mixed-Mode Combustion Assisted by Partial Fuel Stratification in a Spark-Ignition Engine

Partial fuel stratification (PFS) is a promising fuel injection strategy to improve the stability of lean combustion by applying a small amount of pilot injection right before spark timing. Mixed-mode combustion, which makes use of end-gas autoignition following conventional deflagration-based combustion, can be further utilized to speed up the overall combustion. In this study, PFS-assisted mixed-mode combustion in a lean-burn direct injection spark-ignition (DISI) engine is numerically investigated using multi-cycle large eddy simulation (LES). A previously developed hybrid G-equation/well-stirred reactor combustion model for the well-mixed operation is extended to the PFS-assisted operation. The experimental spray morphology is employed to derive spray model parameters for the pilot injection. The LES-based model is validated against experimental data and is further compared with the Reynolds-averaged Navier–Stokes (RANS)-based model. Overall, both RANS and LES predict the mean pressure and heat release rate traces well, while LES outperforms RANS in capturing the cycle-to-cycle variation (CCV) and the combustion phasing in the mass burned space. Liquid and vapor penetrations obtained from the simulations agree reasonably well with the experiment. Detailed flame structures predicted from the simulations reveal the transition from a sooting diffusion flame to a lean premixed flame, which is consistent with experimental findings. LES captures more wrinkled and stretched flames than RANS. Finally, the LES model is employed to investigate the impacts of fuel properties, including heat of vaporization (HoV) and laminar burning speed (SL). Combustion phasing is found more sensitive to SL than to HoV, with a larger fuel property sensitivity of the heat release rate from autoignition than that from deflagration. Moreover, the combustion phasing in the PFS-assisted operation is shown to be less sensitive to SL compared with the well-mixed operation.

fuel property sensitivity↗

Laminar-to-turbulent flame transition and cycle-to-cycle variations in large eddy simulation of spark-ignition engines

This paper investigates the effect of laminar-to-turbulent flame transition modeling on the prediction of cycle-to-cycle variations (CCVs) in large eddy simulation (LES) of spark-ignition (SI) engines. A laminar-to-turbulent flame transition model that describes the non-equilibrium sub-filter flame speed evolution during an early stage of flame kernel growth is developed. In the present model, the flame transition is characterized by the flame kernel size at which the flame transition ends, defined here as the flame transition scale. The proposed model captures the effects that variations in a turbulent flow field have on the evolution of early-stage burning rates, through variations in the flame transition scale. The proposed flame transition model is combined with the front propagation formulation (FPF) method and a spark-ignition model to predict CCVs in a gasoline direct injection SI engine. It is found that multi-cycle LES with the proposed flame transition model reproduces experimentally-observed CCVs satisfactorily. When the transition model is not considered or when variations in the transition process are neglected, CCVs are significantly under-predicted for the case considered here. These results indicate the importance of modeling the laminar-to-turbulent flame transition and the effect of turbulence on the transition process, when predicting CCVs, under certain engine conditions. The LES results are also used to analyze sources for variations in the flame transition. It is found, for the present engine case, that the most important source is the cycle-to-cycle variation in the turbulence dissipation rate, which is used to measure the strength of turbulence in the proposed model, near a spark plug. The large-scale velocity field and the variations of the laminar flame speed due to the mixture composition and thermal stratification are also found to be important factors to contribute to the variations in the flame transition.

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CFD modeling of near-wall combustion and unburned methane prediction in natural gas spark ignition engines

Natural gas-powered engines play a critical role in gas drilling, compression, and transmission sectors, but methane (CH 4 ) from engine combustion slip can be significant over their lifespan, contributing to atmospheric pollution and signaling reduced engine efficiency. Here, to address this challenge, computational fluid dynamics (CFD) simulations offer valuable insights into the in-cylinder combustion process, enabling the optimization of combustion strategies and engine designs to minimize unburned CH 4 slip. This study aims to evaluate and improve combustion models for simulating the combustion process and predicting unburned CH 4 concentrations in natural gas spark-ignition (SI) engines, including engines that are part of combined reformer-engine systems. Specifically, the performance of two flamelet-based combustion models—the Extended Coherent Flame Model (ECFM) and the G-equation model—was assessed using experimental engine data collected under varying excess-air ratio (λ) conditions and fuel compositions, including natural gas and syngas blends. In addition, to enhance the predictive capabilities of the G-equation model, a flame-wall interaction (FWI) sub-model was integrated into its framework. The effects of its model parameters, such as quenching and influence distance, on combustion behavior and unburned methane predictions were analyzed in detail. The ECFM tended to predict delayed combustion phasing under diluted mixture conditions, resulting in overprediction of unburned CH 4 concentrations. In contrast, the G-equation model provided reasonable predictions of combustion pressure, while representing higher the CH 4 reduction rate across the operating condition compared to experimental data. Incorporating the FWI sub-model—with the quenching distance calculated based on a pressure-dependent relation (P -0.48 ) and a fixed influence distance of 1.5 mm—further improved the G-equation model’s accuracy in predicting CH 4 reduction rates without compromising its ability to simulate the combustion process.

Combustion model↗

Assessing the Impact of a Novel TBC Material on Heat Transfer in a Spark Ignition Engine through 3D CFD-FEA Co-Simulation Routine

Thermal barrier coatings (TBCs) have been of interest since the 1970s for application in internal combustion (IC) engines. Thin TBCs exhibit a temperature swing phenomenon wherein wall temperatures dynamically respond to the transient working-gas temperature throughout the engine cycle, thus reducing the temperature difference driving the heat transfer. Determining these varying wall temperatures is necessary to evaluate and study the effect of coatings on wall heat transfer. This study focuses on developing a 3D computational fluid dynamics (CFD)-finite element analysis (FEA) coupled simulation, or co-simulation, routine to determine the wall temperatures of a piston coated with a thin TBC layer subject to spark ignition combustion heat flux. A CONVERGE 3D-CFD model was used to simulate the combustion process in a single-cylinder, light-duty experimental spark ignition (SI) engine. Transient piston heat transfer analysis was conducted using ABAQUS, a FEA package, under the simulated combustion heat flux load. The effect of the temperature swing phenomenon due to this TBC layer was observed in a CFD simulation by implementing the FEA results as the piston thermal boundary conditions. The boundary conditions were passed between the CFD and FEA tools until a quasi-steady state solution was achieved. Furthermore, a reduction in wall heat transfer was observed due to a reduced temperature difference between the wall and the working gas.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modeling Ethanol-Blend Fuel Sprays under Direct-Injection Spark-Ignition Engine Conditions

Computational modeling of fuel-injection and fuel-impingement processes was carried out to provide insight into previous experimental results obtained from a direct-injection spark-ignition research engine operated with various ethanol and aromatic fuel blends. Seven model fuels were evaluated using both single- and split-injection strategies. Model results showed that droplet vaporization enriched the concentrations of aromatic species in the liquid phase, especially those with low vapor pressure, and ethanol-containing fuels altered droplet sizes and led to increased liquid-phase mass in the cylinder. For the spray-modeling conditions studied, most of the injected fuel remained in the liquid phase, which would be expected to result in more fuel impingement on cylinder or piston surfaces. Fuel impinging on lower cylinder-temperature surfaces was found to create wall films that could interact with the piston during the compression stroke. Fuel impinging on hotter piston-temperature surfaces vaporized more readily, but for fuels with high ethanol and aromatic content, wall films remained and were highly concentrated with lower vapor pressure and aromatic compounds. These films could lead to pool fires during combustion and therefore significant particulate matter emissions.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

Learning reference governor for cycle-to-cycle combustion control with misfire avoidance in spark-ignition engines at high exhaust gas recirculation–diluted conditions

Cycle-to-cycle feedback control is employed to achieve optimal combustion phasing while maintaining high levels of exhaust gas recirculation by adjusting the spark advance and the exhaust gas recirculation valve position. The control development is based on a control-oriented model that captures the effects of throttle position, exhaust gas recirculation valve position, and spark timing on the combustion phasing. Under the assumption that in-cylinder pressure information is available, an adaptive extended Kalman filter approach is used to estimate the exhaust gas recirculation rate into the intake manifold based on combustion phasing measurements. The estimation algorithm is adaptive since the cycle-to-cycle combustion variability (output covariance) is not known a priori and changes with operating conditions. A linear quadratic regulator controller is designed to maintain optimal combustion phasing while maximizing exhaust gas recirculation levels during load transients coming from throttle tip-in and tip-out commands from the driver. During throttle tip-outs, however, a combination of a high exhaust gas recirculation rate and an overly advanced spark, product of the dynamic response of the system, generates a sequence of misfire events. In this work, an explicit reference governor is used as an add-on scheme to the closed-loop system in order to avoid the violation of the misfire limit. The reference governor is enhanced with model-free learning which enables it to avoid misfires after a learning phase. Experimental results are reported which illustrate the potential of the proposed control strategy for achieving an optimal combustion process during highly diluted conditions for improving fuel efficiency.

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