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At least 199 records · Page 11

Fuel reid vapor pressure level and ethanol content on stochastic preignition, effects at steady and unsteady engine operation

The present work investigates relations between fuel Reid vapor pressure (RVP) and biofuel (ethanol) content on stochastic preignition (SPI) at both sustained steady-state engine operation and following load transients. This work stems from in-field observations that automotive original equipment manufacturers have observed consistent seasonal increases in United States customer drivability complaints and warranty claims during September and October where SPI is suspected to be responsible. The seasonal timing of these events coincides with the United States seasonal fuel property changeover initiating on September 15 each year, where fuel RVP increases. To explore potential linkage between fuel RVP and SPI the present study employs engine SPI experiments coupled with laboratory spray measurements of fuels with RVPs of 8, 12, and 16 psi in both E10 (10% ethanol) and E25 (25% ethanol) fuels. Engine results are partitioned into fuel RVP and ethanol content effects on SPI in steady-state, sustained high-load engine operation and unsteady-state low- to high-load transitions, where off-engine spray vessel patternation and tip penetration results help to elucidate the observed fuel effects on SPI. A boosted direct-injected, spark-ignition engine was fueled with three market relevant E10 and E25 fuels with RVPs of 8, 12, and 16 to characterize the interplay between winter fuels and abnormal combustion behavior. The steady-state work shows that for high-load, steady-state engine operation, SPI is directly linked to fuel retention, which was found to be dependent on fuel distillation. The unsteady-state engine operation work shows that following low-to high-load transitions, SPI can occur from a memory of fuel property effects at low-load operation. Specifically, the fuel RVP effect on fuel spray collapse at low loads was found to correlate with SPI with a more than 95% confidence interval following low- to high-engine-load transitions. Results suggest that fuel-wall impingement at low-load operation could carry over into high-load transitions and generate SPI events following low- to high-load transitions.

09 BIOMASS FUELS↗

Investigation of the end-gas autoignition process in natural gas engines and evaluation of the methane number index

Engine knock and misfire are barriers to pathways leading to high-efficiency Spark-Ignited (SI) Natural Gas (NG) engines. The general tendency to knock is highly dependent on engine operating conditions and the fuel reactivity. The problem is further complicated by the wide range of chemical reactivity in pipeline quality NG, represented by the Methane Number (MN) (65< MN<95). Understanding the underlying phenomena responsible for engine knock can support the development of predictive tools capable of identifying knock onset/intensity as well as a fuel’s propensity to knock, allowing engine manufacturers to expand the knock envelope and design more efficient/robust SI NG engines. Additionally, there is an opportunity for increased efficiency by controlling levels of end-gas autoignition if this can be predicted and controlled. This work focuses on the development of a novel methodology to understand/predict a fuel’s propensity to knock. This methodology is based on the charge fraction undergoing autoignition, namely fractional end-gas autoignition (F-EGAI), and was developed based on first order laminar flame speeds and ignition delay analysis combined with a 0-D homogeneous batch reactor model. This methodology proved to be suitable to predict a fuel’s propensity to knock, even under conditions when light knock was observed. The simple modeling approach was used to explain the results from a series of MN tests with multiple NG compositions exhibiting a wide range of reactivity compositions and providing insight on why fuels of very different chemical compositions can have the same MN. Finally, a CFD model was developed was used to confirm the methodology capability and provide further insights in the physical and chemical phenomena behind end gas autoignition.

42 ENGINEERING↗

An experimental and modeling study on autoignition of 2-phenylethanol and its blends with n-heptane

2-Phenylethanol (2-PE) is an aromatic alcohol with high research octane number, high octane sensitivity, and a potential to be produced using biomass. Considering that 2-PE can be used as a fuel additive for boosting the anti-knocking quality of gasoline in spark-ignition engines and as the low reactivity fuel or fuel component in dual-fuel reactivity controlled compression ignition (RCCI) engines, it is of fundamental and practical interest to understand the autoignition chemistry of 2-PE, especially at low-to-intermediate temperatures (<1000 K). Based upon the experimental ignition delay time (IDT) results of neat 2-PE obtained from our previous rapid compression machine (RCM) investigation and the literature shock tube study, a detailed chemical kinetic model of 2-PE is developed herein, covering low-to-high temperature regimes. Besides, RCM experiments using binary fuel blends of 2-PE and n-heptane (nC7) are conducted in this work to investigate the nC7/2-PE blending effects, as they represent a dual-fuel system for RCCI operations. Furthermore, the newly developed 2-PE model is merged with a well-validated nC7 kinetic model to generate the current nC7/2-PE binary blend model. Overall, the consolidated model reasonably predicts the experimental IDT data of neat 2-PE and nC7/2-PE blends, as well as captures the experimental effects of pressure, equivalence ratio, and blending ratio on autoignition. Finally, model-based chemical kinetic analyses are carried out to understand and identify the controlling chemistry accounting for the observed blending effects in RCM experiments. In conclusion, the analyses reveal that nC7 enhances 2-PE autoignition via providing extra $\dot{O}$H radicals to the shared radical pool, while the diminished nC7 promoting effect on 2-PE autoignition with increasing temperature is due to the negative temperature coefficient characteristics of nC7.

2-phenlyethanol↗

Development of a high temperature pyrolysis mechanism for cyclopentanone, a potential biofuel derived from biomass

Cyclopentanone (CPO) is a promising biofuel for spark-ignition engines due to its ring strain and high auto-ignition resistance. The Department of Energy has identified CPO as a potential biofuel candidate because of its unique chemical properties. Understanding CPO decomposition is crucial to building a high-temperature combustion model. In this study, we present a comprehensive kinetic model for high-temperature pyrolysis of CPO with verified results from high-pressure shock tube (HPST) measurements. The time histories of carbon monoxide (CO), ethylene (C2H4), and CPO absorbances over the temperature range of 1156-1416 K and 8.53-10.06 atm were measured. A corresponding kinetic model was generated using the Reaction Mechanism Generator (RMG) with the parameters of dominant pathways from either previous studies or quantum calculation within current work. The final model containing 821 species and 79,859 reactions exhibited a good agreement with the experimental results. In this study, the C2H4/CO ratio was used as an essential factor to validate the model and to prove that radical-involved bimolecular pathways were as significant as unimolecular decomposition of CPO. The rate of production (ROP) analysis showed that H radicals play major roles in both primary reactions and product pyrolysis. The insights from this work can be used to generate a better CPO combustion model and help evaluate CPO as a biofuel. Such understanding can also be helpful when proposing pyrolysis or combustion models for other biofuels.

cyclopentanone, reaction mechanism, pyrolysis, sho↗

Low Size, Weight, and Power Neuromorphic Computing to Improve Combustion Engine Efficiency

Neuromorphic computing offers one path forward for AI at the edge. However, accessing and effectively utilizing a neuromorphic hardware platform is non-trivial. In this work, we present a complete pipeline for neuromorphic computing at the edge, including a small, inexpensive, low-power, FPGA-based neuromorphic hardware platform, a training algorithm for designing spiking neural networks for neuromorphic hardware, and a software framework for connecting those components. We demonstrate this pipeline on a real-world application, engine control for a spark-ignition internal combustion engine. We illustrate how we connect engine simulations with neuromorphic hardware simulations and training software to produce hardware-compatible spiking neural networks that perform engine control to improve fuel efficiency. We present initial results on the performance of these spiking neural networks and illustrate that they outperform open-loop engine control. We also give size, weight, and power estimates for a deployed solution of this type.

Schuman, Catherine↗

Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators

Dilute combustion using exhaust gas recirculation (EGR) presents a cost-effective method for increasing the efficiency of spark-ignition (SI) engines. However, the maximum amount of EGR that can be used at a given condition is limited by a rapid increment of cycle-to-cycle variability (CCV). This study describes a methodology to design a model-based stochastic optimal controller to adjust the cycle-to-cycle fuel injection quantity in order to reduce CCV and further extend the dilute limit. Given the complexity and chaotic nature of combustion events, the controller was enhanced with online learning in order to identify the statistical properties of combustion efficiency, which are needed to generate predictions for next-cycle events. This study showed that a kernel density estimator (KDE) can be used to learn the combustion properties in real time and can be incorporated into the feedback policy in order to calculate the optimal control command. Experimental results suggested that the dilute limit can be extended from 18.5% to 21% EGR fraction at an operating condition relevant for highway cruising. Additionally, the proposed controller can achieve a large CCV reduction with less fuel enrichment compared to previous methods, overall contributing to an increase in 0.2% indicated fuel conversion efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

Investigating the Combustion Performance of Dual Fuel Combustion with Diesel and Port Injected Hydrogen in a Large Bore Locomotive Engine

The heavy-duty transportation sector has primarily relied on conventional diesel combustion engines given their reliability and high thermal efficiency relative to spark ignition engines, but increased focus on reducing greenhouse gas emissions has led to investigation into alternative fuels. Gaseous hydrogen fuel has garnered a great deal of recent interest in the engine community given it has zero carbon, but hydrogen is not available at the scale and cost that petroleum fuels are currently available, and this is a barrier to adoption for industries that are looking to decarbonize their operations. Because of the fuel flexibility provided, dual fuel technology offers a pathway for some industries to adopt hydrogen as a fuel source while maintaining sufficient flexibility in times and locations where the new fuel is not yet available. This computational study investigates dual fuel combustion in a large bore locomotive engine architecture using direct injected diesel and port injected gaseous hydrogen fuel. With an optimal port fuel injection configuration from previous work, simulations of varying substitution ratio, compression ratio, manifold air temperature, diesel injection timing, and diesel injection pressure were performed to understand their effect on combustion performance. Results indicated that both increased substitution ratio and higher intake air temperature accelerates hydrogen flame propagation and can result in high peak cylinder pressures. Additionally, diesel injection timing and injection pressure were demonstrated as effective methods for controlling dual fuel combustion heat release rates.

ODonnell, Patrick Christopher↗

Numerical Investigation of Ammonia/n-Heptane Dual-Fuel Spray Flames Using Large Eddy Simulations

Diesel engines are extensively used in heavy-duty transportation, power generation, and marine vehicles due to their superior thermal efficiency and extended high-load operability compared to spark ignition (SI) engines. However, combustion in diesel engines is generally characterized by locally rich fuel–air mixtures and high combustion temperatures, causing significant amounts of soot and NO x emissions from these engines. Utilizing carbon-free alternative fuels and enhancing fuel efficiency represent promising strategies to mitigate greenhouse gas (GHG) and other emissions in the heavy-duty transportation sector. In this context, ammonia (NH 3 ), as a hydrogen carrier, has received significant attention as a viable substitute for hydrocarbon fuels due to its carbon-free composition, relatively high energy density, and well-established infrastructure. Many previous studies have considered combustion and emission characteristics of ammonia-hydrocarbon fuel blends in engines and simplified flames. But, detailed investigations on the effects of ammonia on the performance of hydrocarbon fuels under engine conditions are lacking. In the present study, we perform large eddy simulations (LES) of the ignition and flame processes in a constant-volume combustion reactor, where n-heptane is injected in an ammonia/air ambient mixture in a diesel-like environment. A detailed and validated reaction mechanism containing 302 species and 1981 reactions is employed. The Engine Combustion Network Spray H experimental data is used to validate the spray model under both non-reacting and reacting conditions. Dual-fuel combustion is simulated using the well-stirred reactor (WSR) approach. Results are presented for two spray cases: (1) single fuel (SF) with n-heptane injected into a mixture of air and combustion products and (2) dual-fuel (DF) with the injection of n-heptane in a mixture of air, ammonia, and combustion products. It is observed that the presence of ammonia has a significant effect on the ignition and flame development processes. With ammonia addition, both the first- and second-stage ignition delay times increase, but the effect of ammonia on the second-stage ignition is significantly more prominent. In addition, the ignition kernel size and growth rate decrease noticeably. For SF spray, the main ignition is characterized by multiple ignition kernels near the spray tip, whereas for DF spray, a single relatively small ignition kernel forms and grows slowly in the downstream direction. The flame development and the final quasi-steady flame structure are also modified due to ammonia. Here, the outcome of this research would enable a better understanding of ammonia–diesel dual-fuel spray flame behavior and guide the development of associated engine combustion strategies.

ammonia↗

FASTSim™ (Future Automotive Systems Technology Simulator) [SWR-20-101 and SWR-12-07]

The Future Automotive Systems Technology Simulator (FASTSim™) provides a simple way to compare powertrains and estimate the impact of technology improvements on light-, medium-, and heavy-duty vehicle efficiency, performance, cost, and battery life. This extremely fast simulation tool features a streamlined user interface and can rapidly perform a variety of tasks using basic computing resources: • less than 0.1 second to simulate second-by-second standard duty cycles • less than 10 seconds to estimate vehicle efficiency, fuel economy, acceleration, battery life, and cost • less than 5 minutes to perform powertrain comparisons of efficiency and cost. FASTSim models a variety of vehicle powertrains and fuel converter types: • Conventional vehicles - spark ignition, Atkinson, diesel, and hybrid diesel • Electric-drive vehicles - hybrid, plug-in hybrid, and all-electric • Hydrogen fuel cell vehicles. The default model includes a variety of vehicles and duty cycles and an option for adding additional vehicles and custom cycles: • Packaged with more than 20 vehicles • User interface enables addition of more vehicles • Includes standard U.S. drive cycles as well as European and Japanese cycles. FASTSim is available for download in Microsoft Excel and Python formats here: https://www.nrel.gov/transportation/fastsim.html

Baker, Chad↗

Assessment of an E10 gasoline surrogate: Qualitative and quantitative comparisons of in-cylinder spray morphology

A minimum-component gasoline fuel surrogate that captures both chemical and physical behaviors of a full-distillate fuel is needed for high-fidelity CFD simulations. This study evaluates gasoline spray characteristics in a direct-injection spark-ignition engine under motored operation. Two fuels are compared; PACE-20, which is a 9-component surrogate formulation of RD5-87, is compared with its target fuel RD5-87, which is a full-boiling range research grade E10 gasoline. The spray morphologies of both fuels are recorded for a centrally-located direct-injection 8-hole spray subject to intake air cross-flow during the early part of the intake stroke. High-speed imaging recorded scattered light of the side and axial projections of the liquid spray. Quantitative metrics were developed and employed to facilitate comparison of spray morphologies as well as to identify the transition in spray morphology due to flash boiling. This paper builds on a previous study of RD5-87 where coolant temperature (20°C–100°C), in-cylinder pressure (40–110 kPa), engine speed (650–1950 rpm), and injection pressure (60–180 bar) were systematically changed to span operating conditions with and without flash boiling. Images of the PACE-20 morphology are selected for a sub-set of operating conditions from the previous study where distinctive morphology changes occurred. Visual inspection of the images and quantitative metrics demonstrate that the PACE-20 spray morphology is equivalent to that of the RD5-87 in most cases. The exception was for changes in the ambient-gas pressure where the flash-boiling transition occurred at ∼5 kPa higher in-cylinder pressure for PACE-20. Three empirical metrics, Merging Index, Asymmetry, and Flash Index are proposed here and they were found to be useful both as quantitative comparisons of the fuel morphologies, and for identifying the transition in spray morphology due to flash boiling.

Kim, Namho↗

Measurement of needle and armature dynamics in a gasoline direct injector by high-speed neutron imaging

In modern spark ignition engines, precise delivery of fuel with gasoline direct injection has become increasingly important in the effort to meet ever stricter efficiency and emissions regulations. Use of multiple small close-coupled injections has become more common in attempt to precisely control fuel distribution in the cylinder, but these strategies are hindered by nonlinear injection effects due to operation in the ballistic region of the solenoid-operated valve and due to armature bounce at the end of injection. Understanding the internal dynamics of the injector is crucial to minimizing and controlling non-linearity and shot-to-shot variation, but the experimental techniques available to date are capable only of tracking the position of either the top of the needle (via laser sensors or by monitoring current and voltage in the solenoid coil) or the bottom of the needle (via transparent nozzles or high-speed x-ray imaging). Furthermore, a complete picture of the axial and radial motion of valve needle has until now remained elusive. In this work, we present high-speed ensemble neutron transmission imaging of an entire 8-hole gasoline direct injector operating at 200 bar, allowing for both visualization and quantification of the actuation dynamics including lift and wobble of the valve ball, oscillation and bending of the valve needle, lift, rocking, and bounce of the armature, compression of the springs, and radial swelling of the solenoid during energization. Because neutrons offer high penetration through the metal injector while also being sensitive to the 1 H nuclei in fuel molecules, it is also possible to simultaneously see the fluid dynamics of the injection process, including filling of the sac volume, emanation of the spray through the nozzle holes and into the downstream gas, and the formation and evolution of fuel films on the tip of the injector and the walls of the spray container.

33 ADVANCED PROPULSION SYSTEMS↗

Reinforcement learning applied to dilute combustion control for increased fuel efficiency

To reduce the modeling burden for control of spark-ignition engines, reinforcement learning (RL) has been applied to solve the dilute combustion limit problem. Q-learning was used to identify an optimal control policy to adjust the fuel injection quantity in each combustion cycle. A physics-based model was used to determine the relevant states of the system used for training the control policy in a data-efficient manner. The cost function was chosen such that high cycle-to-cycle variability (CCV) at the dilute limit was minimized while maintaining stoichiometric combustion as much as possible. Experimental results demonstrated a reduction of CCV after the training period with slightly lean combustion, contributing to a net increase in fuel conversion efficiency of 1.33%. To ensure stoichiometric combustion for three-way catalyst compatibility, a second feedback loop based on an exhaust oxygen sensor was incorporated into the fuel quantity controller using a slow proportional-integral (PI) controller. The closed-loop experiments showed that both feedback loops can cooperate effectively, maintaining stoichiometric combustion while reducing combustion CCV and increasing fuel conversion efficiency by 1.09%. Finally, a modified cost function was proposed to ensure stoichiometric combustion with a single controller. In addition, the learning period was shortened by half to evaluate the RL algorithm performance on limited training time. Experimental results showed that the modified cost function could achieve the desired CCV targets, however, the learning time was reduced by half and the fuel conversion efficiency increased only by 0.30%.

33 ADVANCED PROPULSION SYSTEMS↗

In-cylinder spray evolution in a motored central-injection gasoline engine: Imaging and simulating the effects of flash-boiling and intake crossflow

Accurate predictions of fuel spray behavior and mixture formation in simulations of direct-injection spark-ignition (DISI) engines are fundamental to ensure proper description of all subsequent processes including ignition, combustion, and emissions. In this work, the spray evolution in a single-cylinder optical DISI engine was studied experimentally and numerically with the goal of enabling predictive computational fluid dynamics (CFD) modeling of in-cylinder sprays. The authors explored a wide range of operating conditions characterized by several fuel injection temperatures and engine speeds, using a well-characterized nine-component gasoline surrogate known as PACE-20. The effect of flash boiling and intake crossflow on the spray is discussed, with a focus on evaluating the ability of the spray models to capture highly transient spray behavior. In the experiments, the fuel temperature was varied between 20°C and 80°C, allowing for non-flash- to flash-boiling transition to emerge with enhanced flashing intensity at the highest temperatures. Spray collapse resulted in vapor-rich regions, owing to the locally lower inertia of the fluid. Varying the engine speed from 650 to 1950 rpm promoted increasingly more turbulent in-cylinder crossflow which interacted with the spray during the injection event and resulted in enhanced spray dispersion. The CFD model was able to capture the spray morphology transition at different fuel temperatures and engine speeds adequately. Further, it is shown that the spray breakup model could capture the transitional spray behavior induced by flash boiling atomization and intake flow via proper initialization of the spray cone angle and calibration of the spray models’ constants.

33 ADVANCED PROPULSION SYSTEMS↗

Microbial production of high octane and high sensitivity olefinic ester biofuels

Abstract Background Advanced spark ignition engines require high performance fuels with improved resistance to autoignition. Biologically derived olefinic alcohols have arisen as promising blendstock candidates due to favorable octane numbers and synergistic blending characteristics. However, production and downstream separation of these alcohols are limited by their intrinsic toxicity and high aqueous solubility, respectively. Bioproduction of carboxylate esters of alcohols can improve partitioning and reduce toxicity, but in practice has been limited to saturated esters with characteristically low octane sensitivity. If olefinic esters retain the synergistic blending characteristics of their alcohol counterparts, they could improve the bioblendstock combustion performance while also retaining the production advantages of the ester moiety. Results Optimization of Escherichia coli isoprenoid pathways has led to high titers of isoprenol and prenol, which are not only excellent standalone biofuel and blend candidates, but also novel targets for esterification. Here, a selection of olefinic esters enhanced blendstock performance according to their degree of unsaturation and branching. E. coli strains harboring optimized mevalonate pathways, thioester pathways, and heterologous alcohol acyltransferases (ATF1, ATF2, and SAAT) were engineered for the bioproduction of four novel olefinic esters. Although prenyl and isoprenyl lactate titers were limited to 1.48 ± 0.41 mg/L and 5.57 ± 1.36 mg/L, strains engineered for prenyl and isoprenyl acetate attained titers of 176.3 ± 16.0 mg/L and 3.08 ± 0.27 g/L, respectively. Furthermore, prenyl acetate (20% bRON = 125.8) and isoprenyl acetate (20% bRON = 108.4) exhibited blend properties comparable to ethanol and significantly better than any saturated ester. By further scaling cultures to a 2-L bioreactor under fed-batch conditions, 15.0 ± 0.9 g/L isoprenyl acetate was achieved on minimal medium. Metabolic engineering of acetate pathway flux further improved titer to attain an unprecedented 28.0 ± 1.0 g/L isoprenyl acetate, accounting for 75.7% theoretical yield from glucose. Conclusion Our study demonstrated novel bioproduction of four isoprenoid oxygenates for fuel blending. Our optimized E. coli production strain generated an unprecedented titer of isoprenyl acetate and when paired with its favorable blend properties, may enable rapid scale-up of olefinic alcohol esters for use as a fuel blend additive or as a precursor for longer-chain biofuels and biochemicals.

09 BIOMASS FUELS↗

Spark-Assisted HCCI Residential CHP

A transformative small spark ignition (SI) internal combustion (IC) engine fueled with natural gas was developed for combined heat and power (CHP) applications using a combination of cycle simulations, computational fluid dynamics (CFD) modeling, and engine experiments. The resulting 1 kW CHP engine was demonstrated to achieve 36.1% brake thermal efficiency (BTE) while meeting aggressive exhaust emissions targets using a low-cost three-way catalyst. Starting from a “clean-sheet” design, modeling tools were used to select the optimal engine parameters and operating characteristics. The disruptive technologies developed for the CHP system have a target lifetime of at least 10 years. The engine cost at volume of 10,000 units was estimated to be $\$$1,050. A combination of experimental and simulation results were used to identify a path to the program target of 38.6% BTE. Base engine design parameters (i.e., displacement, speed, bore, stroke, valve timings, and compression ratio) were optimized to reduce friction, heat transfer, and exhaust losses. The base clean sheet prototype engine achieved 32% BTE. Optimization of the lube oil and coolant temperatures added 1.8% BTE. The addition of exhaust gas recirculation added 1.1% BTE. Novel thermal barrier coatings (TBCs) developed over the course of the project added 1.2% BTE. Further improvements in engine friction reduction (1.3% BTE) and improved combustion (1.2% BTE) are estimated to meet the program target 38.6% BTE, while also meeting the stringent criteria pollutant emissions targets.

42 ENGINEERING↗

AOI 5 Improved Efficiency of Medium- and Heavy-Duty Natural Gas and Propane (LPG) Engines

Spark-ignited heavy-duty (HD) natural gas engines typically experience efficiency losses at part-load operation due to throttling requirements needed to maintain stoichiometric combustion. A substantial portion of medium- and heavy-duty engine operation occurs in this low-load region, resulting in increased brake-specific carbon dioxide emissions and reduced overall efficiency. This project designed, developed and demonstrated cylinder deactivation (CDA) technology on an HD natural gas engine to mitigate these losses. CDA enables selective deactivation of cylinders, reducing pumping losses while maintaining required torque output and meeting vehicle noise, vibration, and harshness (NVH) targets. The project objectives were successfully achieved, demonstrating up to 12% improvement in fuel consumption over the next generation HD NG engine on key low loaded HD cycles and maintained compliance with 0.02 g/hp-hr NO x emissions with comparable or better vibrations to current product. These results confirm that CDA technology can substantially improve the fuel efficiency and environmental performance of heavy-duty natural gas engines, reinforcing their potential as a low-carbon bridge solution in the transition toward zero-emission transportation technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Sensor System and Observer Algorithm Co-Design For Modern Internal Combustion Engine Air Management Based on H2 Optimization

This paper outlines a novel sensor selection and observer design algorithm for linear time-invariant systems with both process and measurement noise based on H 2 optimization to optimize the tradeoff between the observer error and the number of required sensors. The optimization problem is relaxed to a sequence of convex optimization problems that minimize the cost function consisting of the H 2 norm of the observer error and the weighted l 1 norm of the observer gain. An LMI formulation allows for efficient solution via semi-definite programing. The approach is applied here, for the first time, to a turbo-charged spark-ignited engine using exhaust gas circulation to determine the optimal sensor sets for real-time intake manifold burnt gas mass fraction estimation. Simulation with the candidate estimator embedded in a high fidelity engine GT-Power model demonstrates that the optimal sensor sets selected using this algorithm have the best H 2 estimation performance. Sensor redundancy is also analyzed based on the algorithm results. This algorithm is applicable for any type of modern internal combustion engines to reduce system design time and experimental efforts typically required for selecting optimal sensor sets.

Zhang, Xu↗

Reducing Sample Loss in Measurement of Heat of Vaporization of Ethanol/Gasoline Blends by Differential Scanning Calorimetry/Thermogravimetric Analysis

Higher gasoline Heat of Vaporization (HOV) can enable higher compression-ratio direct injection spark ignition engines by providing evaporative cooling that effectively increases fuel knock resistance. Methods to directly measure this fuel property in complex gasoline samples are not well developed. The objective of the present study was to further improve a Differential Scanning Calorimetry/Thermogravimetric Analyzer (DSC/TGA) method to measure the total and partial HOV of gasoline. Ten market gasoline samples were chosen to have a wide range of properties to assess the method's capability across the entire volatility range with an emphasis on understanding how well the method captures the initial 10 percent (%) of sample evaporation and how much sample is left unevaporated at the end of the experiment. Modifications to the sample preparation/introduction method as well as to the instrument itself were made to reduce initial sample losses which included measurements of the HOV at 10 degrees C and 5 degrees C (in a cold chamber) as well as under (uncontrolled) ambient conditions. Experimental results from the DSC/TGA were compared to calculated total HOV results based on Detailed Hydrocarbon Analysis (DHA). Results from the two methods agreed very well with the difference being 5% or less in almost every case. In addition, the repeatability of the method was investigated by analyzing samples in triplicate at the three temperatures investigated. One valuable conclusion from the study was that the lower temperatures of 10 degrees C and 5 degrees C enabled more reproducible measurements for both total and partial HOV. This improved precision may be caused by the fact that temperature control in the cold chamber was more reliable than the ambient laboratory temperature control. Additionally, cold chamber experiments, due to ergonomic limitations, did not allow for the use of a lid on the sample pan. The reproducibility of the evaporation rate was found to be highly dependent on the pan/lid fit which can vary significantly such that elimination of the lid improved measurement precision while operation at sub-ambient temperature slowed the evaporation rate. Results detailing sample preparation and instrument modifications as well as a detailed comparison of total and partial HOV results are presented.

ADVANCED PROPULSION SYSTEMS,BIOMASS FUELS↗