Electric train energy consumption modeling

Journal Article · Mon May 01 00:00:00 EDT 2017 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2017.02.058· OSTI ID:1427870

Wang, Jinghui ^[1]; Rakha, Hesham A. ^[1]

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1. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Transportation Inst. and Center for Sustainable Mobility

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.

• Research Organization: PARC, Palo Alto, CA (United States)
• Sponsoring Organization: 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)
• Grant/Contract Number: AR0000612
• OSTI ID: 1427870
• Alternate ID(s): OSTI ID: 1414493
• Journal Information: Applied Energy, Vol. 193, Issue C; ISSN 0306-2619
• Publisher: Elsevier
• Country of Publication: United States
• Language: English

Related Subjects

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
42 ENGINEERING
97 MATHEMATICS AND COMPUTING
Electric train
Energy consumption model
Regenerative braking efficiency
Rail transit simulation