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Parameter Identification of SiC MOSFET Half-Bridge Converters Using a Multi-Objective Optimization Method
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DOI：10.3390/electronics14224458.png)
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Abstract
En 中文
Silicon carbide (SiC) power converters are attracting increasing interest due to their significant advantages in terms of efficiency, switching speed, and greater temperature tolerance compared to traditional silicon-based converters. Tools to improve the design process, such as those to predict the switching behavior of silicon carbide-based power converters, can be of great help, e.g., in studying critical electrical/thermal stress in power devices. This work aims to present an effective multi-objective optimization method to identify the main parasitic parameters of a SiC half-bridge power converter related to the board layout and device packaging. This goal was achieved by minimizing the errors between the system responses carried out by the simulated power converter and the measurements collected from a limited number of experimental tests. The feasibility and effectiveness of the method are verified by tests performed on a 1200 V, 75 A, SiC half-bridge converter. Although this methodology has been validated for a specific converter topology, it can be extended to model more complex power converter structures.
Keywords:
genetic algorithm
power converter
parasitic inductances
SiC MOSFET
optimization
modeling
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