IET Intelligent Transport Systems (Jun 2023)

An energy‐efficient train control approach with dynamic efficiency of the traction system

  • Chengcheng Fu,
  • Pengfei Sun,
  • Jiahui Zhang,
  • Keqin Yan,
  • Qingyuan Wang,
  • Xiaoyun Feng

DOI
https://doi.org/10.1049/itr2.12351
Journal volume & issue
Vol. 17, no. 6
pp. 1182 – 1199

Abstract

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Abstract The efficiency of the train traction system (TTS) changes dynamically with operating conditions. In this paper, a more realistic dynamic efficiency model of TTS is established considering the power flow and non‐linear loss of TTS. Based on the real model, the optimal control problem of the train with the minimum electric power consumption on the grid side is constructed. The optimal control condition (OCC) and corresponding control force are derived based on the Pontryagin maximum principle (PMP). A dynamic programming algorithm (DP2) with the OCC curve as the state space is designed to obtain optimal results. The proposed model and the method are validated by the comparison of conventional dynamic programming (DP1) and automatic train operation (ATO) measured data. The simulation results show that compared with the traditional TTS constant efficiency model, considering that the TTS dynamic efficiency model has a better energy‐saving effect, and the designed DP2 algorithm has a more obvious energy‐saving effect than DP1.

Keywords