Abstract
For this paper we develop an electric train energy consumption modeling framework considering instantaneous regenerative braking efficiency in support of a rail simulation system. The model is calibrated with data from Portland, Oregon using an unconstrained non-linear optimization procedure, and validated using data from Chicago, Illinois by comparing model predictions against the National Transit Database (NTD) estimates. The results demonstrate that regenerative braking efficiency varies as an exponential function of the deceleration level, rather than an average constant as assumed in previous studies. The model predictions are demonstrated to be consistent with the NTD estimates, producing a predicted error of 1.87% and -2.31%. The paper demonstrates that energy recovery reduces the overall power consumption by 20% for the tested Chicago route. Furthermore, the paper demonstrates that the proposed modeling approach is able to capture energy consumption differences associated with train, route and operational parameters, and thus is applicable for project-level analysis. The model can be easily implemented in traffic simulation software, used in smartphone applications and eco-transit programs given its fast execution time and easy integration in complex frameworks.
- Authors:
- Wang, Jinghui[1]; Rakha, Hesham A.[1]
+ Show Author Affiliations
- Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Transportation Inst. and Center for Sustainable Mobility
- Publication Date:
- Research Org.:
- PARC, Palo Alto, CA (United States)
- Sponsoring Org.:
- USDOE Advanced Research Projects Agency - Energy (ARPA-E); Transportation for Livability by Integrating Vehicles and the Environment (TranLIVE); Georgia Inst. of Technology, Atlanta, GA (United States)
- OSTI Identifier:
- 1427870
- Alternate Identifier(s):
- OSTI ID: 1414493
- Grant/Contract Number:
- AR0000612
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Applied Energy
- Additional Journal Information:
- Journal Volume: 193; Journal Issue: C; Journal ID: ISSN 0306-2619
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 42 ENGINEERING; 97 MATHEMATICS AND COMPUTING; Electric train; Energy consumption model; Regenerative braking efficiency; Rail transit simulation
Citation Formats
- MLA
- APA
- Chicago
- BibTeX
Wang, Jinghui, and Rakha, Hesham A. Electric train energy consumption modeling. United States: N. p., 2017. Web. doi:10.1016/j.apenergy.2017.02.058.
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Wang, Jinghui, & Rakha, Hesham A. Electric train energy consumption modeling. United States. https://doi.org/10.1016/j.apenergy.2017.02.058
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Wang, Jinghui, and Rakha, Hesham A. Mon . "Electric train energy consumption modeling". United States. https://doi.org/10.1016/j.apenergy.2017.02.058. https://www.osti.gov/servlets/purl/1427870.
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@article{osti_1427870,
title = {Electric train energy consumption modeling},
author = {Wang, Jinghui and Rakha, Hesham A.},
abstractNote = {For this paper we develop an electric train energy consumption modeling framework considering instantaneous regenerative braking efficiency in support of a rail simulation system. The model is calibrated with data from Portland, Oregon using an unconstrained non-linear optimization procedure, and validated using data from Chicago, Illinois by comparing model predictions against the National Transit Database (NTD) estimates. The results demonstrate that regenerative braking efficiency varies as an exponential function of the deceleration level, rather than an average constant as assumed in previous studies. The model predictions are demonstrated to be consistent with the NTD estimates, producing a predicted error of 1.87% and -2.31%. The paper demonstrates that energy recovery reduces the overall power consumption by 20% for the tested Chicago route. Furthermore, the paper demonstrates that the proposed modeling approach is able to capture energy consumption differences associated with train, route and operational parameters, and thus is applicable for project-level analysis. The model can be easily implemented in traffic simulation software, used in smartphone applications and eco-transit programs given its fast execution time and easy integration in complex frameworks.},
doi = {10.1016/j.apenergy.2017.02.058},
journal = {Applied Energy},
number = C,
volume = 193,
place = {United States},
year = {Mon May 01 00:00:00 EDT 2017},
month = {Mon May 01 00:00:00 EDT 2017}
}
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Works referenced in this record:
Energy-saving train scheduling diagram for automatically operated electric railway
journal, November2015
- Watanabe, Shoichiro; Koseki, Takafumi
- Journal of Rail Transport Planning & Management, Vol. 5, Issue 3
- DOI: 10.1016/j.jrtpm.2015.10.004
Sustainable urban rail systems: Strategies and technologies for optimal management of regenerative braking energy
journal, November2013
- González-Gil, Arturo; Palacin, Roberto; Batty, Paul
- Energy Conversion and Management, Vol. 75
- DOI: 10.1016/j.enconman.2013.06.039
Optimization of target speeds of high-speed railway trains for traction energy saving and transport efficiency improvement
journal, December2011
- Feng, Xuesong
- Energy Policy, Vol. 39, Issue 12
- DOI: 10.1016/j.enpol.2011.08.051
Study on the maximum operation speeds of metro trains for energy saving as well as transport efficiency improvement
journal, November2011
- Feng, Xuesong; Mao, Baohua; Feng, Xujie
- Energy, Vol. 36, Issue 11
- DOI: 10.1016/j.energy.2011.09.004
Power-based electric vehicle energy consumption model: Model development and validation
journal, April2016
- Fiori, Chiara; Ahn, Kyoungho; Rakha, Hesham A.
- Applied Energy, Vol. 168
- DOI: 10.1016/j.apenergy.2016.01.097
Modeling and Simulation of Electric and Hybrid Vehicles
journal, April2007
- Gao, David Wenzhong; Mi, Chris; Emadi, Ali
- Proceedings of the IEEE, Vol. 95, Issue 4
- DOI: 10.1109/JPROC.2006.890127
Demonstrating a Bottom-Up Framework for Evaluating Energy and Emissions Performance of Electric Rail Transit Options
journal, January2014
- Gbologah, Franklin E.; Xu, Yanzhi; Rodgers, Michael O.
- Transportation Research Record: Journal of the Transportation Research Board, Vol. 2428, Issue 1
- DOI: 10.3141/2428-02
Comparison of Emissions from Light Rail Transit and Bus Rapid Transit
journal, January2005
- Puchalsky, Christopher M.
- Transportation Research Record: Journal of the Transportation Research Board, Vol. 1927, Issue 1
- DOI: 10.1177/0361198105192700104
Comparison of Emissions from Light Rail Transit, Electric Commuter Rail, and Diesel Multiple Units
journal, January2006
- Messa, Christina A.
- Transportation Research Record: Journal of the Transportation Research Board, Vol. 1955, Issue 1
- DOI: 10.1177/0361198106195500104
Energy Consumption and Emissions of High-Speed Trains
journal, January2010
- Álvarez, Alberto García
- Transportation Research Record: Journal of the Transportation Research Board, Vol. 2159, Issue 1
- DOI: 10.3141/2159-04
Optimal Train Operation for Minimum Energy Consumption Considering Track Alignment, Speed Limit, and Schedule Adherence
journal, September2011
- Kim, Kitae; Chien, Steven I-Jy
- Journal of Transportation Engineering, Vol. 137, Issue 9
- DOI: 10.1061/(ASCE)TE.1943-5436.0000246
Modeling and optimizing energy-efficient manual driving on high-speed lines
journal, September2012
- Sicre, Carlos; Cucala, Asunción P.; Fernández, Antonio
- IEEJ Transactions on Electrical and Electronic Engineering, Vol. 7, Issue 6
- DOI: 10.1002/tee.21782
A Subway Train Timetable Optimization Approach Based on Energy-Efficient Operation Strategy
journal, June2013
- Su, Shuai; Li, Xiang; Tang, Tao
- IEEE Transactions on Intelligent Transportation Systems, Vol. 14, Issue 2
- DOI: 10.1109/tit*.2013.2244885
A systems approach to reduce urban rail energy consumption
journal, April2014
- González-Gil, A.; Palacin, R.; Batty, P.
- Energy Conversion and Management, Vol. 80
- DOI: 10.1016/j.enconman.2014.01.060
An energy-efficient scheduling and speed control approach for metro rail operations
journal, June2014
- Li, Xiang; Lo, Hong K.
- Transportation Research Part B: Methodological, Vol. 64
- DOI: 10.1016/j.trb.2014.03.006
Vehicle lightweighting vs. electrification: Life cycle energy and GHG emissions results for diverse powertrain vehicles
journal, August2014
- Lewis, Anne Marie; Kelly, Jarod C.; Keoleian, Gregory A.
- Applied Energy, Vol. 126
- DOI: 10.1016/j.apenergy.2014.03.023
GIS-driven analysis of e-mobility in urban areas: An evaluation of the impact on the electric energy grid
journal, July2014
- De Gennaro, Michele; Paffumi, Elena; Scholz, Harald
- Applied Energy, Vol. 124
- DOI: 10.1016/j.apenergy.2014.03.003
Preliminary experimental evaluation of a four wheel motors, batteries plus ultracapacitors and series hybrid powertrain
journal, February2011
- Rambaldi, Lorenzo; Bocci, Enrico; Orecchini, Fabio
- Applied Energy, Vol. 88, Issue 2
- DOI: 10.1016/j.apenergy.2010.08.008
Power Conversion and Control for Fuel Cell Systems in Transportation and Stationary Power Generation
journal, July2015
- Rajashekara, Kaushik; Rathore, Akshay K.
- Electric Power Components and Systems, Vol. 43, Issue 12
- DOI: 10.1080/15325008.2015.1034383
Modeling Fuel Consumption of Hybrid Electric Buses: Model Development and Comparison with Conventional Buses
journal, January2016
- Wang, Jinghui; Rakha, Hesham A.
- Transportation Research Record: Journal of the Transportation Research Board, Vol. 2539, Issue 1
- DOI: 10.3141/2539-11
Review of Regional Locomotive Emission Modeling and the Constraints Posed by Activity Data
journal, January2009
- Gould, Gregory; Niemeier, Debbie
- Transportation Research Record: Journal of the Transportation Research Board, Vol. 2117, Issue 1
- DOI: 10.3141/2117-04
Stationary and on-board storage systems to enhance energy and cost efficiency of tramways
journal, October2014
- Ceraolo, M.; Lutzemberger, G.
- Journal of Power Sources, Vol. 264
- DOI: 10.1016/j.jpowsour.2014.04.070
Energetic optimization of regenerative braking for high speed railway systems
journal, December2016
- Frilli, Amedeo; Meli, Enrico; Nocciolini, Daniele
- Energy Conversion and Management, Vol. 129
- DOI: 10.1016/j.enconman.2016.10.011
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Assessment of Modernization of Electric Multiple Units - Case Study
book, September2019
- Wojciechowski, Jerzy; Łukasik, Zbigniew; Jakubowski, Czesław
- Research Methods and Solutions to Current Transport Problems: Proceedings of the International Scientific Conference Transport of the 21st Century, 9– 12th of June 2019, Ryn, Poland, p. 457-465
- DOI: 10.1007/978-3-030-27687-4_46
Assessment of Energy Intensity of the Drive for Traction Power Supply System
book, May2019
- Nezevak, Vladislav; Cheremisin, Vasily; Shatokhin, Andrey
- International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018: Volume 1, p. 524-538
- DOI: 10.1007/978-3-030-19756-8_50
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