Adaptive Eco-Driving Strategy and Feasibility Analysis for Electric Trains with Onboard Energy Storage Devices

Chaoxian Wu, Bin Xu, Shaofeng Lu*, Fei Xue, Lin Jiang, Minwu Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)

Abstract

With the rapid progress in railway electrification and energy storage technologies, onboard energy storage devices (OESDs) have been widely utilized in modern railway systems to reduce energy consumption. This article aims to develop the optimal driving strategy of electric trains with three popular types of energy storage devices, namely supercapacitors, flywheels, and Li-ion batteries, as the OESD to minimize the net energy consumption. With the given OESD investment cost, the dynamic power limits of different types of OESDs are fully considered to optimize the dynamic discharge/charge behavior of the OESD in the train operation. The case studies investigate the train operation on fully electrified railways, discontinuously electrified railways, and catenary-free railways, showing that the optimal eco-driving strategy of the train and discharge/charge behavior of the OESD is significantly different for a different type of OESDs. The obtained train speed, OESDs' state of energy (SOE), power profiles, and energy-saving potential for each type of OESDs under various scenarios are compared comprehensively, and the results also reveal that the flywheel has the best performance for its energy-saving rate ranging from 0.15 %/k $\$ $ to 0.86 %/k $\$ $ , while a Li-ion battery is observed with the weakest performance with the energy-saving rate being only 0.01 %/k $\$ $-0.26 %/k $\$ $. The error rate analysis also confirms a satisfactory modeling accuracy of the proposed method.

Original languageEnglish
Article number9319188
Pages (from-to)1834-1848
Number of pages15
JournalIEEE Transactions on Transportation Electrification
Volume7
Issue number3
DOIs
Publication statusPublished - Sept 2021

Keywords

  • Eco-driving
  • mixed-integer linear programming (MILP)
  • onboard energy storage device (OESD)
  • railway transportation

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