Research On Predictive Control Of Three-level NPC Rectifier For Vacuum Pipeline Maglev Train

The vacuum pipeline maglev train does not have the restrictions of the pantograph network relationship,wheel rail relationship,air resistance and other aspects of wheel rail transit,which can greatly improve the speed of train operation,and has an important innovation and promotion significance for the rapid connection of China's core urban agglomerations and the development of rail transit.Among them,the rectifier system,as a bridge connecting the power grid and the traction and suspension of trains,is the key link in the train power supply system.The system has high requirements for its steady and dynamic performance.In order to realize the multi-objective and high-performance control of the rectifier system of vacuum pipeline maglev traffic,this paper will use the finite set model predictive control algorithm.Aiming at the problems existing in the application of model predictive control in the rectification system of vacuum pipeline maglev transportation,a corresponding improved algorithm is proposed to ensure that while improving the output performance of the system,the calculation time and system loss of the control algorithm are reduced.Firstly,according to the requirements of output voltage,capacity and control of the system,this paper has determined that the parallel three-level diode neutral point clamp(NPC)structure is used as the topology of the rectification system.And the problem of the common control strategies of the large capacity rectifier system are analyzed.In order to improve the control performance of the system,the finite set model predictive control strategy is introduced.Compared with the simulation of the voltage oriented control algorithm,the superiority of the model predictive control applied to the rectification system of vacuum pipeline maglev traffic is verified.This paper analyzes the problems of the traditional model predictive control strategy applied in the rectifier system,mainly including: the main control objectives in the cost function are coupled with each other and affect the output performance;the calculation of the algorithm is large;and the harmonic performance and system loss cannot be coordinated under different working conditions.Secondly,in view of the shortcomings of the above model predictive control strategy,this paper proposes the corresponding improvement strategy.Aiming at the problem of coupling between the two main control targets,current following and neutral point voltage balance in the cost function,this paper removes the neutral point voltage control from the cost function and makes full use of the redundant effect of small vectors to control,which reduces the coupling effect of neutral point voltage balance control and current following.To solve the problem of large calculation of model predictive control algorithm,the control flow is improved in this paper,which can reduce the calculation by 22% in theory.Aiming at the problem of poor harmonic performance under light load of the system,this paper proposes a control strategy with variable weighting factors,which reduces the system loss while ensuring harmonic performance under different operating conditions of the system.Finally,based on MATLAB/Simulink simulation platform,the different control strategies are compared and analyzed,and the correctness of the proposed strategy is verified.Based on the three-level experimental platform,the output performance of VOC strategy is analyzed.Based on the RT-LAB semi-physical experiment platform,the feasibility and effectiveness of the proposed algorithm was verified.