The effect of biofuel blends on the engine performance and emissions of agricultural machines can be extremely complex to predict even if the properties and the effects of the pure substances in the blends can be sourced from the literature. Indeed, on the one hand, internal combustion engines (ICEs) have a high intrinsic operational complexity; on the other hand, biofuels show antithetic effects on engine performance and present positive or negative interactions that are difficult to determine a priori. This study applies the Response Surface Methodology (RSM), a numerical method typically applied in other disciplines (e.g., industrial engineering) and for other purposes (e.g., set-up of production machines), to analyse a large set of experimental data regarding the mechanical and environmental performances of an ICE used to power a farm tractor. The aim is twofold: i) to demonstrate the effectiveness of RSM in quantitatively assessing the effects of biofuels on a complex system like an ICE; ii) to supply easy-to-use correlations for the users to predict the effect of biofuel blends on performance and emissions of tractor engines. The methodology showed good prediction capabilities and yielded interesting outcomes. The effects of biofuel blends and physical fuel parameters were adopted to study the engine performance. Among all possible parameters depending on the fuel mixture, the viscosity of a fuel blend demonstrated a high statistical significance on some system responses directly related to the engine mechanical performances. This parameter can constitute an interesting indirect estimator of the mechanical performances of an engine fuelled with such blend, while it showed poor accuracy in predicting the emissions of the ICE (NOx, CO concentration and opacity of the exhaust gases) due to a higher influence of the chemical composition of the fuel blend on these parameters; rather, the blend composition showed a much higher accuracy in the assessment of the mechanical performance of the ICE.

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There is a growing market demand for small-scale biomass gasifiers that is driven by the economic incentives and the legislative framework. Small-scale gasifiers produce a gaseous fuel, commonly referred to as producer gas, with relatively low heating value. Thus, the most common energy conversion systems that are coupled with small-scale gasifiers are internal combustion engines. In order to increase the electrical efficiency, the operators choose dual fuel engines and mix the producer gas with diesel. The Wiebe function has been a valuable tool for assessing the efficiency of dual fuel internal combustion engines. This study introduces a thermodynamic model that works in parallel with the Wiebe function and calculates the emissions of the engines. This "vis-à-vis" approach takes into consideration the actual conditions inside the cylinders-as they are returned by the Wiebe function-and calculates the final thermodynamic equilibrium of the flue gases mixture. This approach aims to enhance the operation of the dual fuel internal combustion engines by identifying the optimal operating conditions and-at the same time-advance pollution control and minimize the environmental impact.

With the current shift from centralized to more decentralized power production, new opportunities arise for small-scale combined heat and power (CHP) production units like micro gas turbines (mGTs). However, to fully embrace these opportunities, the current mGT technology has to become more flexible in terms of operation—decoupling the heat and power production in CHP mode—and in terms of fuel utilization—showing flexibility in the operation with different lower heating value (LHV) fuels. Cycle humidification, e.g., by performing steam injection, is a possible route to handle these problems. Current simulation models are able to correctly assess the impact of humidification on the cycle performance, but they fail to provide detailed information on the combustion process. To fully quantify the potential of cycle humidification, more advanced numerical models—preferably validated—are necessary. These models are not only capable of correctly predicting the cycle performance, but they can also handle the complex chemical kinetics in the combustion chamber. In this paper, we compared and validated such a model with a typical steady-state model of the steam injected mGT cycle based on the Turbec T100. The advanced one is an in-house MATLAB model, based on the NIST database for the characterization of the properties of the gaseous compounds with the combustion mechanisms embedded according to the Gri-MEch 3.0 library. The validation one was constructed using commercial software (Aspen Plus), using the more advance Redlich-Kwong-Soave (RKS)- Boston-Mathias(BM) property method and assuming complete combustion by using a Gibbs reactor. Both models were compared considering steam injection in the compressor outlet or in the combustion chamber, focusing only on the global cycle performance. Simulation results of the steam injection cycle fueled with natural gas and syngas showed some differences between the two presented models (e.g., 5.9% on average for the efficiency increase over the simulated steam injection rates at nominal power output for injection in the compressor outlet); however, the general trends that could be observed are consistent. Additionally, the numerical results of the injection in the compressor outlet were also validated with steam-injection experiments in a Turbec T100, indicating that the advanced MATLAB model overestimates the efficiency improvement by 25–45%. The results show the potential of simulating the humidified cycle using more advanced models; however, in future work, special attention should be paid to the experimental tuning of the model parameters in general and the recuperator performance in particular to allow correct assessment of the cycle performance.

The (partial or total) substitution of petro-diesel with biodiesel in internal combustion engines (ICEs) could represent a crucial path towards the decarbonization of the energy sector. However, critical aspects are related to the controversial issue of the possible increase in Nitrogen Oxides (NOx) emissions. In such a framework, the proposed study aims at investigating the effects of biodiesel share and injection timing on the performance and NOx emissions of a diesel micro combined heat and power (CHP) system. An experimental campaign has been conducted considering the following operating conditions: (i) a reference standard injection timing (17.2° BTDC), an early injection timing (20.8° BTDC), and a late injection timing (12.2° BTDC); (ii) low (0.90 kW), partial (2.45 kW), and full (3.90 kW) output power load; and (iii) four fuel blends with different biodiesel (B) shares (B0, B15, B30, and B100). Experimental data were also elaborated on thanks to the response surface modelling (RSM) technique, aiming at (i) quantifying the influences of the above-listed variables and their trends on the responses, and (ii) obtaining a set of predictive numerical models that represent the basis for model-based design and optimization procedures. The results show: (i) an overall improvement of the engine performance due to the biodiesel presence in the fuel blend —in particular, B30 and B100 blends have shown peak values in both electrical (29%) and thermal efficiency (42%); (ii) the effective benefits of late SOI strategies on NOx emissions, quantified in an overall average NOx reduction of 27% for the early-to-late injection, and of 16% for the standard-to-late injection strategy. Moreover, it has emerged that the NOx-reduction capabilities of the late injection strategy decrease with higher biodiesel substitution rates; through the discussion of high-prediction-capable, parametric, data-driven models, an extensive RSM analysis has shown how the biodiesel share promotes an increase of NOx whenever it overcomes a calculated threshold that is proportional to the engine load (from about 66.5% to 85.7% of the biodiesel share).

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