Longitudinal train dynamics model for a rail transit simulation system

Wang, Jinghui; Rakha, Hesham A.

doi:10.1016/j.trc.2017.10.011

Title: Longitudinal train dynamics model for a rail transit simulation system

Journal Article · Mon Jan 01 00:00:00 EST 2018 · Transportation Research Part C: Emerging Technologies

DOI:https://doi.org/10.1016/j.trc.2017.10.011· OSTI ID:1427871

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

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

The paper develops a longitudinal train dynamics model in support of microscopic railway transportation simulation. The model can be calibrated without any mechanical data making it ideal for implementation in transportation simulators. The calibration and validation work is based on data collected from the Portland light rail train fleet. The calibration procedure is mathematically formulated as a constrained non-linear optimization problem. The validity of the model is assessed by comparing instantaneous model predictions against field observations, and also evaluated in the domains of acceleration/deceleration versus speed and acceleration/deceleration versus distance. A test is conducted to investigate the adequacy of the model in simulation implementation. The results demonstrate that the proposed model can adequately capture instantaneous train dynamics, and provides good performance in the simulation test. Thus, the model provides a simple theoretical foundation for microscopic simulators and will significantly support the planning, management and control of railway transportation systems.

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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:: 1427871

Alternate ID(s):: OSTI ID: 1693973

Journal Information:: Transportation Research Part C: Emerging Technologies, Vol. 86, Issue C; ISSN 0968-090X

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 13 works

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