Model Predictive Control of Three-Phase Rectifier for Electric Vehicle Charging

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Model predictive control (MPC) can predict the future behavior of the controlled variable by using the system model and this control method is simple and easy to understand and it has good dynamic performance. This paper investigates an MPC strategy to control a three-phase rectifier for the electric vehicle charging application. The prediction model is established based on input filters of the rectifier and is employed to predict the future behavior of the input current. The output voltage can be effectively regulated and maintained. In addition, the input current and input power factor can be controlled at the same time. A traditional PI controller is also implemented for comparative study. The various comparative simulation results obtained in MATLAB/Simulink verify the feasibility and effectiveness of the proposed predictive control.

Original languageEnglish
Title of host publication6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages915-920
Number of pages6
ISBN (Electronic)9781665425575
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2021 - Jinan, China
Duration: 20 Nov 202122 Nov 2021

Publication series

Name6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2021

Conference

Conference6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2021
Country/TerritoryChina
CityJinan
Period20/11/2122/11/21

Free Keywords

  • charging control
  • electric vehicle
  • model predictive control

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization
  • Energy Engineering and Power Technology
  • Control and Systems Engineering

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