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Outline
To achieve lifetime prediction of power modules under actual operating conditions, a power module lifetime prediction method based on a temperature model is proposed. Simulation parameters such as voltage, phase current, power factor, and switching frequency are obtained from the vehicle driving cycle data to calculate module losses. First, the Foster thermal network model is then used to calculate the junction temperature, thereby obtaining the module temperature variation sequence. The rainflow counting method is applied to extract the junction temperature fluctuation sequence. Next, the damage degree of the power module under the corresponding driving cycle is evaluated by combining the lifetime model fitted from power cycling tests. Additionally, the damage degrees of the same module under power generation and electric driving conditions are compared to analyze the performance requirements of the module in different application scenarios. The results show that under a 240 000 km driving cycle, the damage degree in electric driving conditions is significantly higher than in power generation conditions, and an increase in switching frequency exacerbates the damage. This method can effectively support rapid reliability assessment of power modules and provide a basis for module selection and optimization in different application scenarios.
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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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