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The main objective of the work was to develop a comprehensive model of energy consumption simulation of heavy duty vehicles using the VECTO simulation tool. The research issue was the impact of aerodynamic drag and rolling resistance on fuel consumption and emissions under various driving conditions described in four driving cycles: Urban Delivery, Regional Delivery, Urban, and Suburban. Each cycle differed in driving time, distance and average speed to represent different operational scenarios. The methodology involved defining vehicle parameters such as weight, aerodynamic coefficients and tyre rolling resistance. The main findings show that the impact of both aerodynamic drag and rolling resistance on fuel consumption can be efficiently modelled. It has been proven that the proposed modifications to aerodynamic drag and rolling resistance can reduce fuel consumption by more than 8%. The lowest fuel consumption was achieved in the Regional Delivery cycle, while the Urban cycle had the highest fuel consumption due to frequent vehicle stops. The results show that optimization of vehicle design and its performance can significantly improve energy efficiency and reduce emissions. A computational modelling tool such as VECTO can contribute to sustainable transport solutions and improve the efficiency of heavy duty vehicle.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
116--131
Opis fizyczny
Bibliogr. 22 poz., fig., tab.
Twórcy
autor
- Lublin University of Technology, Faculty of Mechanical Engineering, Department of Engineering Thermodynamics, Fluid Mechanics and Aviation Propulsion Systems, Poland
autor
- Graduate, Lublin University of Technology, Faculty of Mechanical Engineering, Poland
autor
- Graduate, Lublin University of Technology, Faculty of Mechanical Engineering, Poland
autor
- Poznan University of Technology, Faculty of Civil Engineering and Transport Institute of Combustion Engines and Powertrains, Poland
Bibliografia
- [1] Bajerlein, M., Karpiuk, W., Kurc, B., Smolec, R., & Waligórski, M. (2024). Refining combustion dynamics: Dissolved hydrogen in diesel fuel within turbulent-flow environments. Energies, 17(11), 2446. https://doi.org/10.3390/en17112446
- [2] Basma, H., Rodríguez, F., Hildermeier, J., Jahn, A., & Project, R. A. (2022). Electrifying last-mile delivery: A total cost of ownership comparison of battery-electric and diesel lorries in Europe. The International Council on Clean Transportation. https://theicct.org/wp-content/uploads/2022/06/tco-battery-diesel-delivery-trucks-jun2022.pdf
- [3] Bayındırlı, C., Akansu, Y. E., & Salman, M. S. (2016). The determination of aerodynamic drag coefficient of truck and trailer model by wind tunnel tests. International Journal of Automotive Engineering and Technologies, 5(2), 53-60. https://doi.org/10.18245/ijaet.11754
- [4] Broekaert, S., Grigoratos, T., Savvidis, D., & Fontaras, G. (2021). Assessment of waste heat recovery for heavy-duty vehicles during on-road operation. Applied Thermal Engineering, 191, 116891. https://doi.org/10.1016/J.APPLTHERMALENG.2021.116891
- [5] Colucci, G., Lerede, D., Nicoli, M., & Savoldi, L. (2023). A dynamic accounting method for CO2 emissions to assess the penetration of low-carbon fuels: application to the TEMOA-Italy energy system optimisation model. Applied Energy, 352, 121951. https://doi.org/10.1016/J.APENERGY.2023.121951
- [6] Curry, T., Liberman, I., Hoffman-Andrews, L., & Lowell, D. (2021, October 15). Reducing aerodynamic drag and rolling resistance from heavy-duty trucks. International Council on Clean Transportation. https://theicct.org/publication/reducing-aerodynamic-drag-and-rolling-resistance-from-heavy-duty-truck
- [7] Czyż, Z., Karpiński, P., Gęca, M., & Ulibarrena Diaz, J. (2018a). The air flow influence on the drag force of a sports car. Advances in Science and Technology Research Journal, 12(2), 121-127. https://doi.org/10.12913/22998624/86213
- [8] Czyż, Z., Karpiński, P., & Sevdim, T. (2018b). Numerical analysis of the drag coefficient of a motorcycle helmet. Applied Computer Science, 14(1), 16-26. https://doi.org/10.23743/acs-2018-02
- [9] De Robbio, R., Cameretti, M. C., & Mancaruso, E. (2022). Investigation by modelling of a plug-in hybrid electric commercial vehicle with diesel engine on WLTC. Fuel, 317, 123519. https://doi.org/10.1016/J.FUEL.2022.123519
- [10] Di Pierro, G., Bitsanis, E., Tansini, A., Bonato, C., Martini, G., & Fontaras, G. (2024). Fuel cell electric vehicle characterisation under laboratory and in-use operation. Energy Reports, 11, 611-623. https://doi.org/10.1016/J.EGYR.2023.12.013
- [11] Eswaranathan, K., Sivakumar, T., De Silva, M. M., & Kumarage, A. S. (2024). Modelling the factors influencing carbon efficiency of consumer choice to promote energy-efficient vehicles. Transport Economics and Management, 2, 130-142 https://doi.org/10.1016/j.team.2024.05.002
- [12] European Commission: Joint Research Centre, Zacharof, N., Broekaert, S., & Fontaras, G. (2021). Future CO2 reducing technologies in VECTO : VECTO technology coverage and market uptake. Publications Office. https://data.europa.eu/doi/10.2760/985739
- [13] Fontaras, G., Rexeis, M., Dilara, P., Hausberger, S., & Anagnostopoulos, K. (2013). The development of a simulation tool for monitoring heavy-duty vehicle CO2 emissions and fuel consumption in Europe. SAE Technical Papers, 6, 2013-24-0150. https://doi.org/10.4271/2013-24-0150
- [14] Grabowski, L. (2021). Modelling research of city bus fuel consumption for different driving cycles. Journal of Physics: Conference Series, 2130, 012001. https://doi.org/10.1088/1742-6596/2130/1/012001
- [15] Khosravi, M., Mosaddeghi, F., Oveisi, M., & Khodayari, A. (2015). Aerodynamic drag reduction of heavy vehicles using append devices by CFD analysis. Journal of Central South University, 22, 4645-4652. https://doi.org/10.1007/s11771-015-3015-7
- [16] Krause, J., Arcidiacono, V., Maineri, L., Broekaert, S., & Fontaras, G. (2023). Calculating heavy-duty vehicle CO2 emission reduction costs for Green Deal scenarios: Extension of the DIONE model. Transportation Research Procedia, 72, 2597-2603. https://doi.org/10.1016/J.TRPRO.2023.11.788
- [17] Na, X., & Cebon, D. (2022). Quantifying fuel-saving benefit of low-rolling-resistance tyres from heavy goods vehicle in-service operations. Transportation Research Part D: Transport and Environment, 113, 103501. https://doi.org/10.1016/J.TRD.2022.103501
- [18] Qiu, Y., Song, S., & Calstart, R. M. (2022, May). Zero-emission lorry real-world performance in us and europe and implications for china. https://globaldrivetozero.org/publication/zero-emission-truck-real-world-performance-in-us-and-europe-and-implications-for-china/
- [19] Seo, J., & Park, S. (2023). Developing an official programme to calculate heavy-duty vehicles CO2 emissions in Korea. Transportation Research Part D: Transport and Environment, 120, 103774. https://doi.org/10.1016/J.TRD.2023.103774
- [20] Tong, F., Wolfson, D., Jenn, A., Scown, C. D., & Auffhammer, M. (2021). Energy consumption and charging load profiles from long-haul lorry electrification in the United States. Environmental Research Infrastructure and Sustainability, 1, 025007. https://doi.org/10.1088/2634-4505/ac186a
- [21] Wahono, B., Santos, W. B., Nur, A., & Amin. (2015). Analysis of range extender electric vehicle performance using vehicle simulator. Energy Procedure, 68, 409-418. https://doi.org/10.1016/j.egypro.2015.03.272
- [22] Zhang, C., Shen, K., Yang, F., & Yuan, C. (2019). Multiphysics modelling of energy intensity and energy efficiency of electric vehicle operation. CIRP procedure, 80, 322-327. https://doi.org/10.1016/j.procir.2019.01.058
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7c8d7354-2bb3-4eae-a296-dffea9f95c79
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