Andrés Melgar

In-cylinder pressure is a fundamental parameter in the design and optimization of internal combustion engines. Therefore, before performing analyses it is essential to correctly obtain and process pressure measurements. However, these signals are often contaminated with high-frequency noise that can compromise combustion diagnostics, especially when cycle-to-cycle variations (CCVs) are significant. This work presents a novel adaptive methodology for filtering in-cylinder pressure signals using a frequency-domain low-pass filter. The proposed approach is able to automatically determine the filter parameters by analyzing the spectral characteristics of the signal, allowing the preservation of both cycle-averaged and CCV information. The method has been validated using pressure traces generated from engine simulations under two extreme operating conditions, with various levels of Additive White Gaussian Noise. For each scenario, the optimal filter configuration was identified by grid searching the cut-off and stopband frequencies to minimize error between the filtered and noise-free signals. The proposed method closely approaches the optimal filter configuration outperforming existing filtering strategies in both signal reconstruction and combustion diagnostics based on the rate of heat release. The results confirm that the proposed filtering strategy effectively retains both cycle-averaged features and cycle-to-cycle variability across a wide range of operating conditions and noise levels.

Thermodynamic criteria as a feedstock selection tool for decentralised downdraft gasifiers coupled to spark-ignition engines are presented in this work. The methodology consists of an energy and exergy analysis of gasification process. The analysis is carried out by computational modelling of the gasification process as a function of biomass type (ultimate analysis, moisture content and heating value) and fuel/air ratio. Considering a system operating with different wood species, analysed parameters are gas heating value, energy and exergy efficiencies and engine fuel quality (EFQ). With a fixed fuel/air ratio (2.6) and moisture content (20%wt), it is highlighted that as the carbon-oxygen molar ratio of wood decreases from 2.0 to 1.78 as model input, reaction temperature increases by 9%, energy and exergy efficiencies diminish by 1.8% and 4.2%, respectively, while EFQ increases by 3.2%. Therefore, for decentralised power plants, biomass should be selected to produce higher EFQ.

This study aimed at presenting a model to simulate downdraft biomass gasification under steady-state or unsteady-state conditions. The model takes into account several processes that are relevant to the transformation of solid biomass into fuel gas, such as drying; devolatilization; oxidation; CO₂, H₂O, and H₂ reduction with char, pressure losses, solid and gas temperature, particle diameter, and bed void fraction evolution; and heat transfer by several mechanisms such as solid–gas convection, bed–wall convection, and radiation in the solid phase. Model validation is carried out by performing experiments in two lab-scale downdraft fixed bed reactors (unsteady-state conditions) and in a novel industrial pilot plant of 400 kW_th–100 kW_e (steady-state conditions). The capability of the model to predict the effect of several factors (reactor diameter, air superficial velocity, and particle size and biomass moisture) on key response variables (temperature field, maximum temperature inside the bed, flame front velocity, biomass consumption rate, and composition and calorific value of the producer gas) is evaluated. For most response variables, a good agreement between experimental and estimated values is attained, and the model is able to reproduce the trend of variation of the experimental results. In general terms, the process performance improves with higher reactor diameter and lesser air superficial velocity, particle size, and moisture content of biomass. The steady-state simulation appears to be a versatile tool for simulating different reactor configurations (preheating systems, variable geometry, and different materials). Copyright © 2013 John Wiley & Sons, Ltd.