Proposal of a Predictive Mixed Experimental- Numerical Approach for Assessing the Performance of Farm Tractor Engines Fuelled with Diesel- Biodiesel-Bioethanol Blends

Abstract

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.

Torque Prediction Model of a CI Engine for Agricultural Purposes Based on Exhaust Gas Temperatures and CFD-FVM Methodologies Validated with Experimental Tests

“…Specifically, the RSM allows the calculation of an explicit polynomial regression-function of a dependent variable (called "response") from a set of input data concerning a set of independent variables (or "factors"), assumed to be measurable and continuous in their own variation ranges. This function is the best approximation, in a limited validity domain (i.e., the first part of the Taylor series up to the third degree), of an unknown real function [69][70][71][72]. In this study, RSM was used to elaborate the effect of different values of parameters on the results and, in particular, to find a combination of values useful to tune the CFD-FVM model (1st sub-procedure about CFD-FVM model tuning).…”

Exploring the Exhaust Emission and Efficiency of Algal Biodiesel Powered Compression Ignition Engine: Application of Box–Behnken and Desirability Based Multi-Objective Response Surface Methodology

“…To establish a robust predictive-optimized model, the findings may be validated via lab-based tests. Bietresato et al [24] successfully employed the RSM to optimize the performance of a biodiesel-bioethanol-diesel powered tractor engine. RSM demonstrated strong prediction abilities and produced interesting results.…”

Injection and Combustion Analysis of Pure Rapeseed Oil Methyl Ester (RME) in a Pump-Line-Nozzle Fuel Injection System

“…In Austria and Germany, neat biodiesel is widely used, whereas in France, Italy, Spain, Sweden, the Czech Republic, and other European countries, fuel blends of diesel fuel with up to 25-30% rapeseed oil methyl ester (RME) are popular [17]. Some reviews on the effects of biodiesel fuels on compression-ignited (CI) engine performance and emissions report the following main outcomes [18][19][20][21][22]: (i) the fuel consumption increases proportionally to the loss of the heating value of the fuel; (ii) the particulate matter (PM) emissions show a consistent reduction; (iii) a minimal or absent loss of power is reported, except when maximum power is required. As regards the brake thermal efficiency (BTE), its value is not significantly affected with biodiesel, but a slight increase or a reduction in the BTE can be noted depending on the engine load, the type of biodiesel, and the blend with mineral diesel fuel [23].…”