Genetic algorithm-based thermal parameters identification for renewable energy system converters

Hanen Messaoudi, Afef Ben Abdelghani-Bennani, Najiba Mrabet Bellaaj, Mohamed Orabi

Abstract


The electro-thermal RC networks are widely used in designing power semiconductor modules; in particular, those used in renewable energy systems for their health monitoring, reliability evaluation, lifetime estimation, and predictive maintenance. This paper proposes a method based on the Genetic Algorithms (GAs) for the identification of the thermal parameters of the IGBT modules used in renewable energy power converters. The proposed identification method doesn’t require any information related to the power module geometric structure or material properties or specific simulator and it doesn’t include any complicated or time-consuming mathematical development or extensive derivation of analytical expressions. It only employs the only information always available in all device datasheet which is the transient thermal impedance from the junction to the case Zth(j-c) curve. The accuracy of the proposed GA-based method was verified in two different ways: first, it was applied to estimate the thermal RC parameters of an IGBT module from INFINEON which are already provided by the manufacturer. Thus, the estimated parameters were compared to the experimental ones, and they are found to be in excellent agreement. Then, the effectiveness of the proposed method was experimentally proved using an infrared (IR) camera.


Keywords


Genetic Algorithm (GA); Infrared (IR) camera; Junction temperature (Tj); solar inverter power modules; Thermal modeling; transient thermal impedance from junction to case (Zth(j-c)).

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v12i3.12594.g8555

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