Thermal stress has been identified as one of the major failure causes in power modules. Generated from the power loss, thermal stress accelerates the degradation of semiconductor devices and downgrades the system reliability. This article presents a finite control set model predictive control (FCS-MPC) oriented to reduce the power loss over the mission profile and relieve the thermal stress in power modules. Conventional control approaches including the switching frequency regulation, the reactive power injection, and the dc-bus voltage adaption show an effective progress. However, the increased control loops and complicated modulation schemes limit the system performance and practical implementation. In the proposed FCS-MPC, a secondary problem formulation is defined to reduce the power loss for the thermal stress reduction in power modules. It is simply integrated with the primary problem formulation in order to achieve the power flow control and power loss reduction simultaneously. An energy-based loss model is proposed for the loss prediction. The impact of the weightings between primary and secondary problem formulations is investigated and a most efficient weighting curve with a weighting-zones strategy is presented to design the proposed FCS-MPC. The proposed FCS-MPC is validated in the simulations and experiments. A 2.5-kW grid-tied inverter prototype is developed for the hardware testing and validation.
|Number of pages||12|
|Journal||IEEE Transactions on Industry Applications|
|State||Published - Jul 1 2020|
Bibliographical noteFunding Information:
Manuscript received November 30, 2019; accepted April 10, 2020. Date of publication April 29, 2020; date of current version July 1, 2020. Paper 2019-IPCC-1477, presented at the 2019 IEEE Energy Conversion Congress and Exposition, Baltimore, MD USA, Sep. 29–Oct. 3, and approved for publication in the IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS by the Industrial Power Converter Committee of the IEEE Industry Applications Society. This work was supported by the North Carolina Renewable Ocean Energy Program, administered by the Coastal Studies Institute. (Corresponding author: Luocheng Wang.) Luocheng Wang, Tao Han, and Tiefu Zhao are with the Department of Electrical and Computer Engineering, Energy Production and Infrastructure Center (EPIC), University of North Carolina at Charlotte, Charlotte, NC 28262 USA (e-mail: email@example.com; firstname.lastname@example.org; email@example.com).
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- Junction temperature estimation
- mission profile
- model predictive control (MPC)
- power loss reduction
- problem formulation
- thermal management
ASJC Scopus subject areas
- Control and Systems Engineering
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering