Fuel consumption mathematical models for road vehicle – A review
Keywords:
Vehicle model, Fuel consumption model, Emissions model, Road transportAbstract
Since the invention of the automobile, engineers and researchers alike have worked towards improving the automobile in various ways from safety, handling and performance to efficiency and durability. As technology in the IT and computing sector evolves into a very helpful tool for detailed calculations, an advantage and possibility for detailed models is there to assist with very detailed assessment on fuel and energy consumption on today’s vehicles. This review is meant to explore in detail what has been achieved by years of joint research through advanced modelling and the following factors such as emissions software and how these models play an important role in sustainable road transport for the masses. The mathematical models also display varying characteristics where models are created striking a balance between complexity, accuracy, and the number of variables to be included.
References
U. EPA, "Global Greenhouse Gas Emissions Data," ed: US EPA, 2016. https://www.epa.gov/regulations-emissions-vehicles-and-engines/regulations-greenhouse-gas-emissions-passenger-cars-and (accessed April 5, 2021).
G.B. Dresser, T.A. Williams, Texas TRANPLAN Application Guide, Texas Transportation Institute, Texas A & M University System, 1992. https://static.tti.tamu.edu/tti.tamu.edu/documents/947-6.pdf (accessed April 5, 2021).
C.-P. Chou, H. Chung, Development of an integrated model for evaluating traffic management plan, in: ASPAC 92: IRF/ARF Asia Pacific Regionsl Road Conference, Gold Coasr, Queensland, Australia, 1992. https://trid.trb.org/view/377095.
W. Lei, H. Chen, L. Lu, Microscopic emission and fuel consumption modeling for light-duty vehi-cles using portable emission measurement system data, World Academy of Science, Engineering and Technology. 66 (2010) 918-925.
F. An, M. Barth, J. Norbeck, M. Ross, Development of comprehensive modal emissions model: op-erating under hot-stabilized conditions, Transportation Research Record, Journal of the Transporta-tion Research Board. 1587 (1997) 52–62. https://doi.org/10.3141/1587-07.
R.B. Noland, M.A. Quddus, Flow improvements and vehicle emissions: effects of trip generation and emission control technology, Transportation Research Part D: Transport and Environment. 11(1) (2006) 1–14. https://doi.org/10.1016/j.trd.2005.06.003.
H. Rakha, K. Ahn, A. Trani, Development of VT-Micro model for estimating hot stabilized light duty vehicle and truck emissions, Transportation Research Part D: Transport and Environment. 9(1) (2004) 49–74. https://doi.org/10.1016/S1361-9209(03)00054-3.
S. Park, H. Rakha, M. Farzaneh, J. Zietsman, D.-W. Lee, Development of fuel and emission models for high speed heavy duty trucks, light duty trucks, and light duty vehicles, in: 13th International IEEE Conference on Intelligent Transportation Systems, 2010:, pp. 25–32. https://doi.org/10.1109/ITSC.2010.5624972.
E.L.a. Herman, Automobile fuel economy on fixed urban driving schedules, Transportation Science. 12(2) (1978) 137–152. http://worldcat.org/oclc/1767714.
R. Akcelik, An interpretation of the parameters in the simple average travel speed model of fuel consumption, Australian Road Research. 15 (1985) 46–49.
H. Yue, Mesoscopic fuel consumption and emission modeling, Virginia Tech, 2008.
Y. Chen, L. Zhu, J. Gonder, S. Young, K. Walkowicz, Data-driven fuel consumption estimation: A multivariate adaptive regression spline approach, Transportation Research Part C: Emerging Tech-nologies. 83 (2017) 134–145. https://doi.org/10.1016/j.trc.2017.08.003.
M. Barth, K. Boriboonsomsin, Real-world carbon dioxide impacts of traffic congestion, Transporta-tion Research Record: Journal of the Transportation Research Board. 2058(1) (2008) 163–171. https://doi.org/10.3141/2058-20.
H. Khayyam, A. Kouzani, K. Khoshmanesh, E. Hu, Power analysis and simulation of a vehicle un-der combined loads, in: Proceedings of the 4th International Green Energy Conference, North China Electric Power University (NCEPU), 2008: pp. 855-871. https://dro.deakin.edu.au/eserv/DU:30018276/kouzani-poweranalysisand-2008.pdf.
M. Hillion, J. Chauvin, O. Grondin, N. Petit, Active combustion control of Diesel HCCI engine: Combustion timing, SAE Technical Paper. (2008) 2008-01-0984. https://doi.org/10.4271/2008-01-0984.
J.C.a.W. Livengood, P.C. Wu, Correlation of auto ignition phenomena in internal combustion en-gines and rapid compression machine, Proceedings of the 5th International Symposium on Combus-tion. 5(1) (1955) 347–356. https://doi.org/10.1016/S0082-0784(55)80047-1.
J.J. Scillieri, J.H. Buckland, J.S. Freudenberg, Reference feedforward in the idle speed control of a direct-injection spark-ignition engine, IEEE transactions on Vehicular Technology. 54(1) (2005) 51–61. https://doi.org/10.1109/TVT.2004.838842.
J. Pu, C. Yin, Optimal control of fuel economy in parallel hybrid electric vehicles, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 221(9) (2007) 1097–1106. https://doi.org/10.1243/09544070JAUTO432.
H.A. Rakha, K. Ahn, W. Faris, K.S. Moran, Simple vehicle powertrain model for modeling intelli-gent vehicle applications, IEEE transactions on intelligent transportation systems. 13(2) (2012) 770–780. https://doi.org/10.1109/TITS.2012.2188517.
O. Orfila, C. Freitas Salgueiredo, G. Saint Pierre, H. Sun, Y. Li, D. Gruyer, S.Glaser, Fast computing and approximate fuel consumption modeling for internal combustion engine passenger cars, Trans-portation Research Part D: Transport and Environment. 50 (2017) 14–25. https://doi.org/10.1016/j.trd.2016.10.016.
D. Gruyer, C. Royere, N. du Lac, G. Michel, J. Blosseville, SiVIC and RTMaps, interconnected plat-forms for the conception and the evaluation of driving assistance systems, in Proceedings of the its world congress, 2006, vol. 10.
O. Orfila, D. Gruyer, V. Judalet, M. Revilloud, Ecodriving performances of human drivers in a vir-tual and realistic world, in: 2015 IEEE Intelligent Vehicles Symposium (IV), 2015: pp. 790–795. https://doi.org/10.1109/IVS.2015.7225781.
Y. Ding, H. Rakha, Trip-based explanatory variables for estimating vehicle fuel consumption and emission rates, Water, Air and Soil Pollution: Focus. 2(5-6) (2002) 61–77. https://doi.org/10.1023/A:1021350310219.
Y.-T. Zhang, C.G. Claudel, M.-B. Hu, Y.-H. Yu, C.-L. Shi, Develop of a fuel consumption model for hybrid vehicles, Energy Conversion and Management. 207 (2020) 112546. https://doi.org/10.1016/j.enconman.2020.112546.
K. Ahn, Modeling light duty vehicle emissions based on instantaneous speed and acceleration lev-els, Virginia Tech, 2002. https://vtechworks.lib.vt.edu/handle/10919/28246.
C. Samaras, D. Tsokolis, S. Toffolo, G. Magra, L. Ntziachristos, Z. Samaras, Enhancing average speed emission models to account for congestion impacts in traffic network link-based simulations, Transportation Research Part D: Transport and Environment. 75 (2019) 197–210. https://doi.org/10.1016/j.trd.2019.08.029.
H. Rakha, K. Ahn, Integration modeling framework for estimating mobile source emissions, Journal of Transportation Engineering. 130(2) (2004) 183–193. https://doi.org/10.1061/(ASCE)0733-947X(2004)130:2(183).
H. Rakha, M. Van Aerde, K. Ahn, A. Trani, Requirements for evaluating traffic signal control im-pacts on energy and emissions based on instantaneous speed and acceleration measurements, Transportation Research Record. 1738(1) (2000) 56–67. https://doi.org/10.3141/1738-07.
F. Froschhammer, D. Mathiak, F. Rabenstein, Hochdynamische prüfstände–ein werkzeug für die insta-tionärapplikation, in ATZ/MTZ Konferenz–Motor, 2006.
F. Froschhammer, M. Schittenhelm, and R. Keppler, BMW high-dynamic engine test benches using SIMPACK real-time models, Simpack News Nov, vol. 9, 2009. https://www.semanticscholar.org/paper/BMW-High-Dynamic-Engine-Test-Benches-using-SIMPACK-Schittenhelm-Keppler/4cfa5e2645a653e62678376bc5358003b8127015 (accessed April 5, 2021).
H.C. Frey, N.M. Rouphail, H. Zhai, T.L. Farias, G.A. Gonçalves, Comparing real-world fuel con-sumption for diesel-and hydrogen-fueled transit buses and implication for emissions, Transporta-tion Research Part D: Transport and Environment. 12(4) (2007) 281–291. https://doi.org/10.1016/j.trd.2007.03.003.
H. Wang, L. Fu, Y. Zhou, H. Li, Modelling of the fuel consumption for passenger cars regarding driving characteristics, Transportation Research Part D: Transport and Environment. 13(7) 2008 479–482. https://doi.org/10.1016/j.trd.2008.09.002.
G.O. Duarte, G.A. Gonçalves, P.C. Baptista, T.L. Farias, Establishing bonds between vehicle certifi-cation data and real-world vehicle fuel consumption–a vehicle specific power approach, Energy Conversion and Management. 92 (2015) 251–265. https://doi.org/10.1016/j.enconman.2014.12.042.
Z. Kan, L. Tang, M.-P. Kwan, X. Zhang, Estimating vehicle fuel consumption and emissions using GPS big data, International Journal of Environmental Research and Public Health. 15(4) (2018) 566. https://doi.org/10.3390/ijerph15040566.
C. Fiori, K. Ahn, H.A. Rakha, Power-based electric vehicle energy consumption model: Model de-velopment and validation, Applied Energy. 168 (2016) 257–268. https://doi.org/10.1016/j.apenergy.2016.01.097
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Progress in Energy and Environment
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
