Title: Modelling and optimisation of train electric drive system based on fuzzy predictive control in urban rail transit

Authors: Yeran Huang; Fang Cao; Bwo-ren Ke; Tao Tang

Addresses: State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing Laboratory of Urban Mass Transit, Beijing Key Laboratory of Urban Mass Transit Automation and Control, China ' State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing Laboratory of Urban Mass Transit, Beijing Key Laboratory of Urban Mass Transit Automation and Control, China ' Department of Electrical Engineering, National Penghu University of Science and Technology, Penghu 880, Taiwan ' State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing Laboratory of Urban Mass Transit, Beijing Key Laboratory of Urban Mass Transit Automation and Control, China

Abstract: This paper establishes an elaborate model of train electric drive system to simulate the train operation process. The transmission loss and train length are taken into account when calculating voltage of contact line and resistance force with equivalent slope. Considering the influence of voltage and slope variation on control performance, we propose original model original control with fixed voltage (OMOC-FV) and original model original control with slope (OMOC-S) to compare with the most commonly used PI control method, i.e., modified model original control (MMOC). Moreover, focusing on variable parameters and complex dynamics of induction motor, a fuzzy predictive control method, called modified model modified control (MMMC), is proposed to track the target speed profile accurately and to achieve the voltage stability. The effectiveness of elaborate model and the performance of MMMC are evaluated based on the data of Beijing Yizhuang line.

Keywords: modelling; train traction systems; fuzzy predictive control; FPC; urban rail transit; URT; optimisation; train electric drives; simulation; transmission loss; train length; contact line voltage; resistance force; equivalent slope; slope variation; fuzzy control; induction motors; motor dynamics; voltage stability; speed profile; China.

DOI: 10.1504/IJSPM.2016.079198

International Journal of Simulation and Process Modelling, 2016 Vol.11 No.5, pp.363 - 373

Received: 29 May 2015
Accepted: 06 Apr 2016

Published online: 21 Sep 2016 *

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