A Decision-Tree-Based Approach to Smoke Spike Detection in a Heavy-Duty Diesel Engine

Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.

Design and Preliminary Results of an Atmospheric-Pressure Model Gas Turbine Combustor Utilizing Varying CO2 Doping Concentration in CH4 to Emulate Biogas Combustion

Utilization of biogas can provide a source of renewable energy in both heat and power generation. Combustion of biogas in land-based gas turbines for power generation is a promising approach to reducing greenhouse gases and US dependence on foreign-source fossil fuels. Biogas is a byproduct from the decomposition of organic matter and consists primarily of CH4 and large amounts of CO2. The focus of this research was to design a combustion device and investigate the effects of increasing levels of CO2 addition to the combustion of pure CH4 with air. Using an atmospheric-pressure, swirl-stabilized dump combustor, emissions data and flame stability limitations were measured and analyzed. In particular, CO2, CO, and NOx emissions were the main focus of the combustion products. Additionally, the occurrence of lean blowout and combustion pressure oscillations, which impose significant limitations in operation ranges for actual gas turbines, was observed. Preliminary kinetic and equilibrium modeling was performed using Cantera and CEA for the CH4/CO2/Air combustion systems to analyze the effect of CO2 upon adiabatic flame temperature and emission levels. The numerical and experimental results show similar dependence of emissions on equivalence ratio, CO2 addition, inlet air temperature, and combustor residence time. (C) 2014 Elsevier Ltd. All rights reserved.