NeTrainSim: a network-level simulator for modeling freight train longitudinal motion and energy consumption

Ahmed S. Aredah, Karim Fadhloun, Hesham A. Rakha

Railway Engineering Science ›› 2024

Railway Engineering Science ›› 2024 DOI: 10.1007/s40534-024-00331-x
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NeTrainSim: a network-level simulator for modeling freight train longitudinal motion and energy consumption

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Abstract

Although train modeling research is vast, most available simulation tools are confined to city- or trip-scale analysis, primarily offering micro-level simulations of network segments. This paper addresses this void by developing the NeTrainSim simulator for heavy long-haul freight trains on a network of multiple intersecting tracks. The main objective of this simulator is to enable a comprehensive analysis of energy consumption and the associated carbon footprint for the entire train system. Four case studies were conducted to demonstrate the simulator’s performance. The first case study validates the model by comparing NeTrainSim output to empirical trajectory data. The results demonstrate that the simulated trajectory is precise enough to estimate the train energy consumption and carbon dioxide emissions. The second application demonstrates the train-following model considering six trains following each other. The results showcase the model ability to maintain safe-following distances between successive trains. The next study highlights the simulator’s ability to resolve train conflicts for different scenarios. Finally, the suitability of the NeTrainSim for modeling realistic railroad networks is verified through the modeling of the entire US network and comparing alternative powertrains on the fleet energy consumption.

Keywords

NeTrainSim / Network train simulation / Train longitudinal motion / Energy consumption / Carbon footprint

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Ahmed S. Aredah, Karim Fadhloun, Hesham A. Rakha. NeTrainSim: a network-level simulator for modeling freight train longitudinal motion and energy consumption. Railway Engineering Science, 2024 https://doi.org/10.1007/s40534-024-00331-x

References

[1.]
Nalley S LaRose A. Annual energy outlook 2022, 2022 Washington U.S Energy Information Administration
[2.]
Association of American Railroads (2021) Freight railroads & climate change. https://www.aar.org/wp-content/uploads/2021/02/AAR-Climate-Change-Report.pdf, Accessed 18 May 2022
[3.]
United States Environmental Protection Agency (EPA) (2023) Fast facts: U.S. transportation sector greenhouse gas emissions 1990–2021. https://www.epa.gov/system/files/documents/2023-06/420f23016.pdf. Accessed 17 May 2022
[4.]
Association of American Railroads. Railroad facts, 2022 New York Watertown
[5.]
García-Álvarez A Perez-Martinez P González-Franco I. Energy consumption and carbon dioxide emissions in rail and road freight transport in Spain: a case study of car carriers and bulk petrochemicals. J Intell Transp Syst, 2012 17 3 233-244
CrossRef Google scholar
[6.]
Iwnicki S Spiryagin M Cole C . Handbook of railway vehicle dynamics, 2019 2 Boca Raton CRC Press
CrossRef Google scholar
[7.]
Wu Q (2017) Optimisations of draft gear designs for heavy haul trains. Dissertation, Central Queensland University
[8.]
Cole C (1999) Longitudinal train dynamics: characteristics, modeling, simulation and neural network prediction for Central Queensland coal trains. Dissertation, Central Queensland University
[9.]
Wu Q Luo S Cole C. Longitudinal dynamics and energy analysis for heavy haul trains. J Mod Transp, 2014 22 3 127-136
CrossRef Google scholar
[10.]
Shabana AA Aboubakr AK Ding L. Use of the non-inertial coordinates in the analysis of train longitudinal forces. J Comput Nonlinear Dyn, 2012 7 1 011001
CrossRef Google scholar
[11.]
Kovalev R Sakalo A Yazykov V . Simulation of longitudinal dynamics of a freight train operating through a car dumper. Veh Syst Dyn, 2016 54 6 707-722
CrossRef Google scholar
[12.]
Qi Z Huang Z Kong X. Simulation of longitudinal dynamics of long freight trains in positioning operations. Veh Syst Dyn, 2012 50 9 1409-1433
CrossRef Google scholar
[13.]
Chen C Han M Han Y. A numerical model for railroad freight car-to-car end impact. Discret Dyn Nat Soc, 2012 2012 927592
CrossRef Google scholar
[14.]
Jin X Luo Y. The mathematic description of features of the friction type draft gears. Roll Stock, 2011 49 1-4(in Chinese)
[15.]
Varazhun I Shimanovsky A Zavarotny A. Determination of longitudinal forces in the cars automatic couplers at train electrodynamic braking. Procedia Eng, 2016 134 415-421
CrossRef Google scholar
[16.]
Evans J Berg M. Challenges in simulation of rail vehicle dynamics. Veh Syst Dyn, 2009 47 8 1023-1048
CrossRef Google scholar
[17.]
Li W Jiang S Jin M. Multi-Objective optimization and weight selection method for heavy haul trains trajectory. IEEE Access, 2022 10 41152-41163
CrossRef Google scholar
[18.]
Wei W Lin Y. Simulation of a freight train brake system with 120 valves. Proc Inst Mech F J Rail Rapid Transit, 2009 223 1 85-92
CrossRef Google scholar
[19.]
Andersen DR, Booth GF, Vithani AR et al (2012) Train energy and dynamics simulator (teds): a state-of-the-art longitudinal train dynamics simulator. In: ASME 2012 Rail Transportation Division Fall Technical Conference, Omaha, pp 57–63
[20.]
Sanborn GG, Heineman JR, Shabana AA (2007) A low computational cost nonlinear formulation for multibody railroad vehicle systems. In: ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Las Vegas, pp 1847–1856
[21.]
Wu Q Cole C Luo S Spiryagin M. A review of dynamics modeling of friction draft gear. Veh Syst Dyn, 2014 52 6 733-758
CrossRef Google scholar
[22.]
Cipek M Pavković D Kljaić Z . Assessment of battery-hybrid diesel-electric locomotive fuel savings and emission reduction potentials based on a realistic mountainous rail route. Energy, 2019 173 1154-1171
CrossRef Google scholar
[23.]
Kirschstein T Meisel F. GHG-emission models for assessing the eco-friendliness of road and rail freight transports. Transp Res Part B Methodol, 2015 73 13-33
CrossRef Google scholar
[24.]
Graver B Frey H. Comparison of locomotive emissions measured during dynamometer versus rail yard engine load tests. Transp Res Rec, 2013 2341 1 23-33
CrossRef Google scholar
[25.]
American railway engineering and maintenance-of-way association (2021) AREMA manual for railway engineering
[26.]
Fadhloun K Rakha H. A novel vehicle dynamics and human behavior car-following model: model development and preliminary testing. Int J Transp Sci Technol, 2020 9 1 14-28
CrossRef Google scholar
[27.]
Wang J Rakha HA. Longitudinal train dynamics model for a rail transit simulation system. Transp Res Part C Emerg Technol, 2018 86 111-123
CrossRef Google scholar
[28.]
Spiryagin M, Wu Q, Cole C et al (2016) Advanced studies on locomotive dynamics behavior utilizing co-simulation between multibody and train dynamics packages. In: CORE 2016, Maintaining the Momentum, Conference on Railway Excellence, Melbourne
[29.]
Hay WW. Railroad engineering, 1991 New York Wiley
[30.]
Brandenburger N Jipp M. Effects of expertise for automatic train operations. Cogn Technol Work, 2017 19 699-709
CrossRef Google scholar
[31.]
Aredah A, Fadhloun K, Rakha HA et al (2022) NeTrainSim: A longitudinal freight train dynamics simulator for electric energy consumption. In: Transportation Research Board Annual Meeting 2022, Washington DC
[32.]
Ahn K Aredah A Rakha H . Simple diesel train fuel consumption model for real-time train applications. Energies, 2023 16 8 3555
CrossRef Google scholar
[33.]
Dion F Rakha H Kang YS. Comparison of delay estimates at under-saturated and over-saturated pre-timed signalized intersections. Transp Res Part B Methodol, 2004 38 2 99-122
CrossRef Google scholar
[34.]
Rakha H Kang YS Dion F. Estimating vehicle stops at undersaturated and oversaturated fixed-time signalized intersections. Transp Res Rec, 2001 1776 1 128-137
CrossRef Google scholar
[35.]
Wang J Ghanem A Rakha H . A rail transit simulation system for multi-modal energy-efficient routing applications. Int J Sustain Transp, 2021 15 3 187-202
CrossRef Google scholar
[36.]
Aredah A Du J Hegazi M . Comparative analysis of alternative powertrain technologies in freight trains: a numerical examination toward sustainable rail transport. Appl Energy, 2024 356 122411
CrossRef Google scholar
[37.]
Aredah A, Fadhloun K, Rakha H et al (2022) NeTrainSim: a network freight train simulator for estimating energy/fuelconsumption. Preprints 2022080518. https://doi.org/10.20944/preprints202208.0518.v1. Accessed 17 May 2022

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