Abstract

Recently, low-frequency oscillation (LFO) has occurred many times in high-speed railways and has led to traction blockades. Some of the literature has found that the stability of the vehicle-grid coupling system could be improved by optimizing the control strategy of the traction line-side converter (LSC) to some extent. In this paper, a model-based predictive current control (MBPCC) approach based on continuous control set in the dq reference frame for the traction LSC for electric multiple units (EMUs) is proposed. First, the mathematical predictive model of one traction LSC is deduced by discretizing the state equation on the alternating current (AC) side. Then, the optimal control variables are calculated by solving the performance function, which involves the difference between the predicted and reference value of the current, as well as the variations of the control voltage. Finally, combined with bipolar sinusoidal pulse width modulation (SPWM), the whole control algorithm based on MBPCC is formed. The simulation models of EMUs’ dual traction LSCs are built in MATLAB/SIMULINK to verify the superior dynamic and static performance, by comparing them with traditional transient direct current control (TDCC). A whole dSPACE semi-physical platform is established to demonstrate the feasibility and effectiveness of MBPCC in real applications. In addition, the simulations of multi-EMUs accessed in the vehicle-grid coupling system are carried out to verify the suppressing effect on LFO. Finally, to find the impact of external parameters (the equivalent leakage inductance of vehicle transformer, the distance to the power supply, and load resistance) on MBPCC’s performance, the sensitivity analysis of these parameters is performed. Results indicate that these three parameters have a tiny impact on the proposed method but a significant influence on the performance of TDCC. Both oscillation pattern and oscillation peak under TDCC can be easily influenced when these parameters change.

Highlights

  • With the rapid development of high-speed railway, alternating current (AC)–direct current (DC)–AC drive electric multiple units (EMUs) and electric locomotives are increasingly put into operation

  • To optimize the control performance of EMUs’ traction drive units, namely dual traction line-side converter (LSC), and suppress low-frequency oscillation (LFO) in vehicle-grid coupling system of high-speed railways, model-based predictive current control (MBPCC) is proposed in order to apply the traction LSC of China Railway high-speed 3 (CRH3) EMUs

  • Simulation verifications, and semi-physical verifications, the performance of MBPCC is demonstrated in comparison to transient direct current control (TDCC), and the advantages of each listed below: (1)

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Summary

Introduction

With the rapid development of high-speed railway, alternating current (AC)–direct current (DC)–AC drive electric multiple units (EMUs) and electric locomotives are increasingly put into operation. In [11], a small-signal frequency domain model of LSC in a dq reference frame was established, and the impact of controller parameters on the stability of the vehicle-grid coupling system was discussed. According to these studies, the vehicle-grid coupling system can be defined as a dynamic stability problem of a large-scale multi-converter system under specific conditions. To solve the LFO in a high-speed railway system, the way of adopting the MPC strategy, based on continuous control set in the traction single-phase LSC, has not yet been tried. LSCs and handle the LFO in vehicle-grid coupling system, a model-based predictive current control (MBPCC) strategy based on a continuous control set is presented for EMUs’ traction LSC control.

Mathematical Model of One Traction Line-Side Converter
Predictive Model of One Traction Line-Side Converter
The Two-Step Prediction
Design of Performance
Simulations of One Traction Drive Unit of Electric Multiple Units
The parameters in the TDCC andand controllers
Start-Operation Process
Sudden-Load-Change Process
Track Performance
System Verification
Analysis of System Parameters
Load Resistance Rload
Equivalent Leakage Inductance L
Equivalent Leakage Inductance L N
18. Waveforms
Conclusions
Full Text
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