Experimental Comparative Study on Performance and Emissions of E85 Adopting Different Injection Approaches in a Turbocharged PFI SI Engine

This study examines the effects of ethanol and gasoline injection mode on the combustion performance and exhaust emissions of a twin cylinder port fuel injection (PFI) spark ignition (SI) engine. Generally, when using gasoline–ethanol blends, alcohol and gasoline are externally mixed with a specified blending ratio. In this activity, ethanol and gasoline were supplied into the intake manifold into two different ways: through two separated low pressure fuel injection systems (Dual-Fuel, DF) and in a blend (mix). The ratio between ethanol and gasoline was fixed at 0.85 by volume (E85). The initial reference conditions were set running the engine with full gasoline at the knock limited spark advance boundary, according to the standard engine calibration. Then E85 was injected and a spark timing sweep was carried out at rich, stoichiometric, and lean conditions. Engine performance and gaseous and particle exhaust emissions were measured. Adding ethanol could remove over-fueling with an increase in thermal efficiency without engine load penalties. Both ethanol and charge leaning resulted in a lowering of CO, HC, and PN emissions. DF injection promoted a faster evaporation of gasoline than in blend, shortening the combustion duration with a slight increase in THC and PN emissions compared to the mix mode.

Using Machine Learning to Analyze Factors Determining Cycle-to-Cycle Variation in a Spark-Ignited Gasoline Engine

In this work, we have applied a machine learning (ML) technique to provide insights into the causes of cycle-to-cycle variation (CCV) in a gasoline spark-ignited (SI) engine. The analysis was performed on a set of large eddy simulation (LES) calculations of a single cylinder of a four-cylinder port-fueled SI engine. The operating condition was stoichiometric, without significant knock, at a load of 16 bar brake mean effective pressure (BMEP), at an engine speed of 2500 rpm. A total of 123 cycles was simulated. Of these, 49 were run in sequence, while 74 were run in parallel. For the parallel approach, each cycle is initialized with its own synthetic turbulent field to generate CCV, as a part of another work performed by us. In this work, we used 3D information from all 123 cycles to compute flame topology and pre-ignition flow-field metrics. We then evaluated correlations between these metrics and peak cylinder pressure (PCP) employing an ML technique called random forest. The computed metrics form the inputs to the random forest model, and PCP is the output. This model captures the effect of all inputs, as well as interactions between them owing to its decision-tree structure. The goal of this work is to demonstrate (as a first step) that ML models can implicitly learn complex relationships between the pre-ignition flow-fields, the flame shapes, and the eventual outcome of the cycle (whether a cycle will be a high or a low cycle).

Influence of Acetone-Butanol-Ethanol (ABE)–Gasoline Blends on Regulated and Unregulated Emissions From a PFI SI Engine

Bio-butanol has been widely investigated as a promising alternative fuel. However, the main issues preventing industrial-scale production of butanol are its relatively low production efficiency and high cost of component recovery from the acetone-butanol-ethanol (ABE) fermentation process. Therefore, ABE has attracted a lot of interest as an alternative fuel for the reason that it not only has positive characteristics of oxygenated fuels, but also reduces the production cost during fermentation. This investigation is focused on the regulated and unregulated emissions of a single cylinder port-fuel injection (PFI) spark-ignition (SI) engine fueled with ABE (volumetric concentration of A:B:E = 3:6:1) and gasoline blends. Blends of gasoline with various ABE content (0 vol.%, 10 vol.%, 20 vol.% ABE referred to as G100, ABE10, ABE20) were used as test fuels. Experiments were performed at an engine speed of 1200 rpm, and at engine loads of 3 and 5 bar brake mean effective pressures (BMEP) and under various equivalence ratios (Φ = 0.83–1.25). Exhaust gases measured included nitrogen oxides (NOX), carbon monoxide (CO) and unburned hydrocarbons (UHC). Additionally, benzene, ethylbenzene, toluene and xylenes (BTEX) concentrations were also measured by a gas chromatograph coupled with a mass spectrometer (GC/MS) and a flame ionization detection (GC/FID). The results show that with an increase of ABE in the blended fuel, there are reductions of UHC, CO and NOx. For the unregulated emissions, ABE addition leads to decreases in benzene, toluene and xylene emissions but an increase in ethylbenzene.

Finite Element Analysis on Frame-Type Hydraulic Press

Hydraulic press is important pressure processing equipment, which has a wide range of applications in production and manufacturing industry. The structure of hydraulic press frame has an extremely significant effect on safety and usability. Against the structure of frame-type hydraulic press in this paper, a solid model has been built with CAD program Pro/E and the hydraulic press frame under working conditions is simulated by finite element simulation program ANSYS. This paper analyses the variation of stress, strain and frame deformation under working conditions, and the dangerous sections of hydraulic press frame can be found under the maximum work load. The research results show: The maximum value of effective strain and effective stress can be found in the screw holes of cylinder port, the maximum value of stress and strain in the direction of hydrocylinder force can be found in the confluence of upright column and lower beam, the maximum value of effective displacement and the displacement in the direction of hydrocylinder force can be found in cylinder port and part of upper beam.

Transient Control of Combustion Phasing and Lambda in a Six-Cylinder Port-Injected Natural-Gas Engine

Fuel economy and emissions are the two central parameters in heavy duty engines. High exhaust gas recirculation rates combined with turbocharging has been identified as a promising way to increase the maximum load and efficiency of heavy duty spark ignition engines. With stoichiometric conditions, a three way catalyst can be used, which keeps the regulated emissions at very low levels. The Lambda window, which results in very low emissions, is very narrow. This issue is more complex with transient operation, resulting in losing brake efficiency and also catalyst converting efficiency. This paper presents different control strategies to maximize the reliability for maintaining efficiency and emissions levels under transient conditions. Different controllers are developed and tested successfully on a heavy duty six-cylinder port injected natural gas engine. Model predictive control was used to control lambda, which was modeled using system identification. Furthermore, a proportional integral regulator combined with a feedforward map for obtaining maximum brake torque timing was applied. The results show that excellent steady-state and transient performance can be achieved.

Transient Control of Combustion Phasing, Lambda in a 6-Cylinder Port-Injected Natural-Gas Engine

Fuel economy and emissions are the two central parameters in heavy duty engines. High EGR rates combined with turbocharging has been identified as a promising way to increase the maximum load and efficiency of heavy duty spark ignition engines. With stoichiometric conditions a three way catalyst can be used which keeps the regulated emissions at very low levels. The Lambda window which results in very low emissions is very narrow. This issue is more complex with transient operation resulting in losing brake efficiency and also catalyst converting efficiency. This paper presents different control strategies to maximize the reliability for maintaining efficiency and emissions levels under transient conditions. Different controllers are developed and tested successfully on a heavy duty 6-cylinder port injected natural gas engine. Model Predictive Control (MPC) was used to control lambda which was modeled using System Identification. Furthermore, a Proportional Integral (PI) regulator combined with a feedforward map for obtaining Maximum Brake Torque (MBT) timing was applied. The results show that excellent steady-state and transient performance can be achieved.