Real-time thermal management for two-level active rectifier with finite control set model predictive control. (October 2021)

• Record Type: Journal Article
• Authors: Ozkan, Gokhan; Hoang, Phuong H.; Ramezani Badr, Payam; Edrington, Chris S.; Papari, Behnaz
• Is Part Of: International journal of electrical power & energy systems. Volume 131(2021)
• Publication Date: 2021-10
• Subjects: Power electronics -- Model predictive control -- Active thermal management -- Controller-hardware-in-the-loop (CHIL); Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2021.107057
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Electro-thermal management improves system reliability by reducing thermal cycling. Finite-control set model predictive control (FCS-MPC) provides multi objective control for power converters. FCS-MPC algorithm is evaluated by using Controller-hardware-in-the-loop (CHIL) instantiation. Abstract: A power electronic converters' reliability is crucial for power systems. The degradation and failure of the switching devices are mainly related to their junction temperature. The temperature fluctuation on a switching device, i.e. the thermal cycling, can be reduced by controlling the losses on the semiconductors, which may cause power quality issues. Increasing the switching frequency can improve the power quality; however, it has a negative impact on the thermal stress for semiconductors. Overall, there is a trade-off between thermal cycling and power quality, and both should be managed to improve the reliability while meeting system requirements. In this paper, a Finite Control Set Model Predictive Control (FCS-MPC) method is proposed to provide electro-thermal control on semiconductor devices by minimizing the power quality issues via selection of the optimum switching states. The proposed algorithm performance is validated by offline simulation and controller-hardware-in-the-loop (CHIL) experimentation.