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Predictive Set Point Modulation Charging of Autonomous Rail Transit Vehicles

Author

Listed:
  • Heng Li

    (School of Computer Science and Engineering, Central South University, Changsha 410083, China)

  • Yu Zhang

    (School of Computer Science and Engineering, Central South University, Changsha 410083, China)

  • Hongtao Liao

    (School of Automation, Central South University, Changsha 410083, China)

  • Jun Peng

    (School of Computer Science and Engineering, Central South University, Changsha 410083, China)

Abstract

Autonomous rail transit (ART) vehicle is a new type of urban rail transportation, which has good development prospects. It is powered by onboard supercapacitors, which are charged at midway stations. It requires short charging time and fast charging speed. Usually, multiple chargers are used in parallel for charging. However, this will cause an overshoot phenomenon during charging, and the overshoot of multiple chargers will be superimposed on the supercapacitor, affecting the stability and life of both supercapacitors and chargers. In this paper, we propose a predictive set point modulation charging method, which can reduce the system’s overshoot and increase the reliability of the system. First, the state-space averaging method is used to establish the electronic physical model of the multicharger system. Secondly, a predictive set point modulation charging control method is designed, and the closed-loop model of the proposed charging system is developed using the buck diagram. The effectiveness of the proposed method is verified through extensive simulation and experiments. The experimental results show that compared with the classical design method, the proposed method can effectively suppress the current overshoot.

Suggested Citation

  • Heng Li & Yu Zhang & Hongtao Liao & Jun Peng, 2020. "Predictive Set Point Modulation Charging of Autonomous Rail Transit Vehicles," Energies, MDPI, vol. 13(19), pages 1-12, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:4992-:d:417701
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