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Electric train energy consumption modeling

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  • Wang, Jinghui
  • Rakha, Hesham A.

Abstract

The paper develops 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.

Suggested Citation

  • Wang, Jinghui & Rakha, Hesham A., 2017. "Electric train energy consumption modeling," Applied Energy, Elsevier, vol. 193(C), pages 346-355.
    • Handle: RePEc:eee:appene:v:193:y:2017:i:c:p:346-355
    DOI: 10.1016/j.apenergy.2017.02.058
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    1. De Gennaro, Michele & Paffumi, Elena & Scholz, Harald & Martini, Giorgio, 2014. "GIS-driven analysis of e-mobility in urban areas: An evaluation of the impact on the electric energy grid," Applied Energy, Elsevier, vol. 124(C), pages 94-116.
    2. Lewis, Anne Marie & Kelly, Jarod C. & Keoleian, Gregory A., 2014. "Vehicle lightweighting vs. electrification: Life cycle energy and GHG emissions results for diverse powertrain vehicles," Applied Energy, Elsevier, vol. 126(C), pages 13-20.
    3. Feng, Xuesong & Mao, Baohua & Feng, Xujie & Feng, Jia, 2011. "Study on the maximum operation speeds of metro trains for energy saving as well as transport efficiency improvement," Energy, Elsevier, vol. 36(11), pages 6577-6582.
    4. Liu, Rongfang (Rachel) & Golovitcher, Iakov M., 2003. "Energy-efficient operation of rail vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(10), pages 917-932, December.
    5. Li, Xiang & Lo, Hong K., 2014. "An energy-efficient scheduling and speed control approach for metro rail operations," Transportation Research Part B: Methodological, Elsevier, vol. 64(C), pages 73-89.
    6. Fiori, Chiara & Ahn, Kyoungho & Rakha, Hesham A., 2016. "Power-based electric vehicle energy consumption model: Model development and validation," Applied Energy, Elsevier, vol. 168(C), pages 257-268.
    7. Gould, Gregory & Niemeier, Debbie A., 2009. "Review of Regional Locomotive Emission Modeling and the Constraints Posed by Activity Data," Institute of Transportation Studies, Working Paper Series qt3gn498w6, Institute of Transportation Studies, UC Davis.
    8. Feng, Xuesong, 2011. "Optimization of target speeds of high-speed railway trains for traction energy saving and transport efficiency improvement," Energy Policy, Elsevier, vol. 39(12), pages 7658-7665.
    9. Rambaldi, Lorenzo & Bocci, Enrico & Orecchini, Fabio, 2011. "Preliminary experimental evaluation of a four wheel motors, batteries plus ultracapacitors and series hybrid powertrain," Applied Energy, Elsevier, vol. 88(2), pages 442-448, February.
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