Predictive Set Point Modulation Charging of Autonomous Rail Transit Vehicles

Heng Li, Yu Zhang, Hongtao Liao and Jun Peng
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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

Energies, 2020, vol. 13, issue 19, 1-12

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.

Keywords: ART; supercapacitor; multiple chargers; overshoot; set point modulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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