FATIGUE ANALYSIS IN MODULAR MULTILEVEL CONVERTER USING RAINFLOW ALGORITHM
Publication Date : 15/04/2021
Modular multilevel converter (MMC) is composed of several semiconductor switches and capacitors. However, these basic components of MMC are fragile especially when operated in harsh environment. As such, the resulting fatigue of the converter need be estimated so that the converter can be replaced before complete failure. One of the parameters that determines the lifetime of the converter is the junction temperature of the semiconductor switches which varies during operation and generates temperature swings. In this paper, an electro-thermal model for estimating the junction temperature of MMC is developed and rainflow algorithm is used to identify the fatigue parameters from the temperature profile; namely temperature swings, mean value of the temperature and the number of temperature cycles. Using these parameters, the number of cycles to failure were computed based on Coffin-Manson-Arrhenius lifetime model. The entire system including the control strategy was simulated in MATLAB® using Simulink® and PLECS® toolboxes. The results show that temperature swing is the main critical stressor of the converter, as such, can be used to plan maintenance or replacement before complete failure occurs. The temperature estimation was validated on a laboratory prototype MMC using type-K thermocouples and KEYSIGHT LXI Agilent 34972A BenchLink Data Logger.
No. of Downloads :