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To solve the difficulty in online life prediction of silicon carbide metal-oxide-semiconductor field-effect transistor (SiC MOSFET) under practical working conditions, a digital implementation method for SiC MOSFET module life prediction based on particle swarm optimization-back propagation (PSO-BP) neural network was proposed. First, the saturation voltage drop of SiC MOSFET was extracted by a saturation voltage drop platform as the temperature-sensitive electric parameter, and a junction temperature prediction scheme based on experimental data was established. Second, a life prediction scheme based on PSO-BP neural network was established by using a power cycling accelerated aging experimental platform to extract the aging characteristic data. Third, the junction temperature prediction scheme and life prediction scheme were transplanted to field programmable gate array to realize the digitization of SiC MOSFET life prediction. Finally, a circuit was designed to verify the proposed method. Experimental results show that the error between the digital junction temperature and real junction temperature was 4.73 ℃, and the percentage of error between the predicted life times and real life times was 4.1%, which proves that the proposed life prediction method is realized digitally and can accurately predict the life times of SiC MOSFET module.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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