Full
Outline
The accurate chip junction temperature prediction of power semiconductor modules is significant for their reliable operation. However, the research about freewheeling diode (FWD) chip junction temperature prediction is not sufficient at present, and the models of temperature sensitive electric parameters and the corresponding evaluation mechanism are lacking. A peak reverse recovery current model is deduced based on the turn-off process of FWD, and the relationship of peak reverse recovery current with bus voltage, load current and junction temperature is established. Then, a parameter identification approach for the peak reverse recovery current model is proposed based on the particle swarm optimization algorithm with random mutation, and the result of double-pulse test is used to extract the model parameters and verify the model. To reduce the model error caused by the linear distribution and linear changes of carriers, the exponential terms of load current and bus voltage are further added, thus optimizing the prediction of peak current. Finally, a junction temperature prediction approach for FWD chips in power semiconductor modules is put forward based on the optimized model, and this approach is more accurate compared with the look-up-table method, indicating that it can satisfy the requirements of FWD junction temperature prediction.
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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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