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

Author

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  • Marco Bietresato

    (Faculty of Science and Technology, Free University of Bozen/Bolzano, Piazza Università 5, Bolzano I-39100, Italy)

  • Carlo Caligiuri

    (Faculty of Science and Technology, Free University of Bozen/Bolzano, Piazza Università 5, Bolzano I-39100, Italy)

  • Anna Bolla

    (Faculty of Science and Technology, Free University of Bozen/Bolzano, Piazza Università 5, Bolzano I-39100, Italy)

  • Massimiliano Renzi

    (Faculty of Science and Technology, Free University of Bozen/Bolzano, Piazza Università 5, Bolzano I-39100, Italy)

  • Fabrizio Mazzetto

    (Faculty of Science and Technology, Free University of Bozen/Bolzano, Piazza Università 5, Bolzano I-39100, Italy)

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 (NO x , 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.

Suggested Citation

  • Marco Bietresato & Carlo Caligiuri & Anna Bolla & Massimiliano Renzi & Fabrizio Mazzetto, 2019. "Proposal of a Predictive Mixed Experimental- Numerical Approach for Assessing the Performance of Farm Tractor Engines Fuelled with Diesel- Biodiesel-Bioethanol Blends," Energies, MDPI, vol. 12(12), pages 1-45, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:12:p:2287-:d:240024
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    References listed on IDEAS

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    Cited by:

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    2. Prabhakar Sharma & Ajay Chhillar & Zafar Said & Saim Memon, 2021. "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," Energies, MDPI, vol. 14(18), pages 1-22, September.
    3. Roberto Fanigliulo & Marcello Biocca & Renato Grilli & Laura Fornaciari & Pietro Gallo & Stefano Benigni & Paolo Mattei & Daniele Pochi, 2022. "Assessment of the Performance of Agricultural Tires Using a Mobile Test Bench," Agriculture, MDPI, vol. 13(1), pages 1-22, December.
    4. Homeyra Piri & Massimiliano Renzi & Marco Bietresato, 2023. "Technical Implications of the Use of Biofuels in Agricultural and Industrial Compression-Ignition Engines with a Special Focus on the Interactions with (Bio)lubricants," Energies, MDPI, vol. 17(1), pages 1-45, December.
    5. Flavio Caresana & Marco Bietresato & Massimiliano Renzi, 2021. "Injection and Combustion Analysis of Pure Rapeseed Oil Methyl Ester (RME) in a Pump-Line-Nozzle Fuel Injection System," Energies, MDPI, vol. 14(22), pages 1-25, November.
    6. Carlo Caligiuri & Marco Bietresato & Angelo Algieri & Marco Baratieri & Massimiliano Renzi, 2022. "Experimental Investigation and RSM Modeling of the Effects of Injection Timing on the Performance and NO x Emissions of a Micro-Cogeneration Unit Fueled with Biodiesel Blends," Energies, MDPI, vol. 15(10), pages 1-19, May.

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