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Model predictive control algorithm for prolonging lifetime of three-phase voltage source convertersopen access

Authors
Nguyen, Minh-HoangKwak, SangshinChoi, Seungdeog
Issue Date
2023
Publisher
Institute of Electrical and Electronics Engineers Inc.
Keywords
Legged locomotion; lifetime; model predictive control; per-phase; Switches; Switching frequency; Switching loss; switching loss; thermal reduction; Thermal stresses; Voltage control
Citation
IEEE Access, v.11, pp 72781 - 72802
Journal Title
IEEE Access
Volume
11
Start Page
72781
End Page
72802
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/67786
DOI
10.1109/ACCESS.2023.3294995
ISSN
2169-3536
Abstract
One of the key goals of power electronics is to reduce losses in three-phase converters in order to increase efficiency and reduce thermal stress, which can lengthen the lifetime of devices. However, the aforementioned studies do not account for the fact that the phase legs of the converter can experience various aging conditions, which reduces the expected lifetime of converter. This paper proposes a minimum loss per-phase method based on predictive control for voltage source inverter, which aims at particularly reducing loss of specific phase leg to increase the lifetime of the entire converter. The output currents will be controlled using predicted reference voltages and predictive zero-sequence voltage injection in the proposed technique. The particular phase leg, which is the most aged leg, will be clamped to the positive and negative dc-link to generate a non-switching region. This will result in the reduction of switching frequency and switching loss of the most aged phase leg in the voltage source inverter, which prolongs the lifetime of the particular phase leg and entire converter. The results of simulation and experimentation are used to confirm the validity of the proposed method and effectiveness in increasing lifetime of converter, where the switching loss of the most aged leg is reduced by up to 85%, and corresponding lifetime increases by about four times compared to the conventional model predictive control method. Author
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Kwak, Sang Shin
창의ICT공과대학 (전자전기공학부)
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