Modeling the Impact of Alternative Fuel Properties on Light Vehicle Engine Performance and Greenhouse Gases Emissions
Technical Paper
2019-01-2308
ISSN: 0148-7191, e-ISSN: 2688-3627
Sector:
Language:
English
Abstract
The present-day transport sector needs sustainable energy solutions. Substitution of fossil-fuels with fuels produced from biomass is one of the most relevant solutions for the sector. Nevertheless, bringing biofuels into the market is associated with many challenges that policymakers, feedstock suppliers, fuel producers, and engine manufacturers need to overcome.
The main objective of this research is an investigation of the impact of alternative fuel properties on light vehicle engine performance and greenhouse gases (GHG). The purpose of the present study is to provide decision-makers with tools that will accelerate the implementation of biofuels into the market. As a result, two models were developed, that represent the impact of fuel properties on engine performance in a uniform and reliable way but also with very high accuracy (coefficients of determination over 0.95) and from the end-user point of view. The inputs of the model are represented by fuel properties, whereas output by fuel consumption (FC). The parameters are represented as percentage changes relative to standard fossil fuel, which is gasoline for spark ignition (SI) engines and diesel for compression ignition (CI) engines. The methodology is based on data-driven black-box modeling (input-output relation). The multilinear regression was performed using the data from driving cycles such as the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) and New European Driving Conditions (NEDC). The FC of SI engines proved to be dependent on mass-based Net Calorific Value (NCV), Research Octane Number (RON), oxygen content and density. However, CI engines performance is affected by NCV, density and Cetane Number (CN). The models were additionally subject to quantitative analysis, where input parameters in both models turned out to be statistically significant (p-value below 5%). Additionally, the validation stage consisted of residual analysis confirmed the accuracy of both models. The GHG part estimates the change of carbon dioxide emissions based on fuel consumption, which represents the tailpipe emissions.
Authors
Topic
Citation
Kroyan, Y., Wojcieszyk, M., Larmi, M., Kaario, O. et al., "Modeling the Impact of Alternative Fuel Properties on Light Vehicle Engine Performance and Greenhouse Gases Emissions," SAE Technical Paper 2019-01-2308, 2019, https://doi.org/10.4271/2019-01-2308.Data Sets - Support Documents
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References
- International Energy Agency , World Energy Balances 2017, Organization for Economic Co-Operation and Development.
- European Commission , “EU Transport in Figures - Statistical Pocketbook,” 2017.
- Zhou, M., Jin, H., and Wang, W. , “A Review of Vehicle Fuel Consumption Models to Evaluate Eco-Driving and Ecorouting,” Transportation Research Part D: Transport and Environment 49:203-218, 2016.
- Kroyan, Y. , “Modeling the Impact of Fuel Properties on Spark Ignition Engine Performance,” 2018.
- Wojcieszyk, M. , “Modeling the Impact of Fuel Properties on Compression Ignition Engine Performance,” 2018.
- Marotta, A. et al. , “Gaseous Emissions from Lightduty Vehicles: Moving from NEDC to the New WLTP Test Procedure,” Environmental Science & Technology 49(14):8315-8322, 2015.
- Keesman, K.J. , System Identification: An Introduction (Springer Science & Business Media, 2011).
- Gavin, H. , “The Levenberg-Marquardt Method for Nonlinear Least Squares Curvefitting Problems,” Department of Civil and Environmental Engineering, Duke University, 2011, 1-15.
- Kalita, M., Muralidharan, M., Subramanian, M., Sithananthan, M. et al. , “Experimental Studies on n-Butanol/Gasoline Fuel Blends in Passenger Car for Performance and Emission,” SAE Technical Paper 2016-01-2264, 2016, https://doi.org/10.4271/2016-01-2264.
- Stansfield, P.A., Bisordi, A., OudeNijeweme, D., Williams, J. et al. , “The Performance of a Modern Vehicle on a Variety of Alcohol-Gasoline Fuel Blends,” SAE Int. J. Fuels Lubr. 5(2):813-822, 2012, https://doi.org/10.4271/2012-01-1272.
- Zhu, R., Hu, J., Bao, X., He, L., Zu, L., Li, Y., and Zhang, M. , “Impact of Alcohol Gasoline on Fuel Consumption and Tailpipe Emissions of a China IV Passenger Car,” in Control Conference (CCC), 2016 35th Chinese IEEE, July 2016, 8795-8800.
- Millo, F., Mallamo, F., Vlachos, T., Ciaravino, C. et al. , “Experimental Investigation on the Effects on Performance and Emissions of an Automotive Euro 5 Diesel Engine Fuelled with B30 from RME and HVO,” SAE Technical Paper 2013-01-1679, 2013, https://doi.org/10.4271/2013-01-1679.
- Armas, O., García-Contreras, R., Ramos, Á., and López, A.F. , “Impact of Animal Fat Biodiesel, GTL, and HVO Fuels on Combustion, Performance, and Pollutant Emissions of a Light-Duty Diesel Vehicle Tested under the NEDC,” Journal of Energy Engineering 141(2):C4014009, 2014.
- Napolitano, P., Beatrice, C., Guido, C., Del Giacomo, N. et al. , “Hydrocracked Fossil Oil and Hydrotreated Vegetable Oil (HVO) Effects on Combustion and Emissions Performance of “Torque-Controlled” Diesel Engines,” SAE Technical Paper 2015-24-2497, 2015, https://doi.org/10.4271/2015-24-2497.
- Stengel, B. and Vium, J.H. , “Synthesis, Characterization, and Use of Hydro-Treated Oils and Fats for Engine Operation,” A Report from the IEA Advanced Motor Fuels Implementing Agreement to Annex, 45, 2015.