Model predictive control with secondary objective functions for power module loss reduction

Luocheng Wang, Tao Han, Tiefu Zhao, Jiangbiao He

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

This paper presents a finite control set model predictive control (FCS-MPC) method to reduce the power module loss while meeting the converter performance requirements. Many modulation-level and system-level loss reduction strategies are proposed by either changing the switching frequency or adjusting the reactive power. However, increased control loops and complicated modulation schemes restrict the system performance and implementation. With the features of model predictive control, FCS-MPC has the capability to achieve several control targets by simultaneously optimizing multiple objective functions. In the proposed FCS-MPC, a secondary objective function is defined to reduce the power loss of semiconductor devices and relieve the thermal stress for power modules. This control mechanism provides the system with not only the straightforward effectiveness, but also maintaining the converter performance requirements. The proposed FCS-MPC is validated in the simulations and experiments. A 2.5-kW PWM rectifier prototype is developed to demonstrate the proposed control method.

Original languageEnglish (US)
Title of host publication2019 IEEE Energy Conversion Congress and Exposition, ECCE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages225-231
Number of pages7
ISBN (Electronic)9781728103952
DOIs
StatePublished - Sep 2019
Externally publishedYes
Event11th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2019 - Baltimore, United States
Duration: Sep 29 2019Oct 3 2019

Publication series

Name2019 IEEE Energy Conversion Congress and Exposition, ECCE 2019

Conference

Conference11th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2019
Country/TerritoryUnited States
CityBaltimore
Period9/29/1910/3/19

All Science Journal Classification (ASJC) codes

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

Keywords

  • Junction temperature estimation
  • Model predictive control
  • Power loading
  • Power loss reduction
  • Thermal management

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