The calibration procedure is mathematically formulated as a constrained non-linear optimization problem. The calibration and validation work is based on data collected from the Portland light rail train fleet. The model can be calibrated without any mechanical data making it ideal for implementation in transportation simulators. The paper develops a longitudinal train dynamics model in support of microscopic railway transportation simulation. 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 = , 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. (Virginia Tech), Blacksburg, VA (United States). 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.

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 paper demonstrates that energy recovery reduces the overall power consumption by 20% for the tested Chicago route. The model predictions are demonstrated to be consistent with the NTD estimates, producing a predicted error of 1.87% and -2.31%. 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 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. For this paper we develop an electric train energy consumption modeling framework considering instantaneous regenerative braking efficiency in support of a rail simulation system.

Run 8 locomotive mods