Estimating Cyclic Thermal Stress in Power Semiconductor Devices
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Solution Overview
Problem
Power electronic devices and systems lack insight into the thermal stress levels of their power semiconductor devices, which can lead to premature component failure due to material fatigue caused by excessive temperature cycling.
Innovation Solution
A method that extracts thermal cycle data from temperature data, determines the thermal cycling operating point of a power semiconductor device, and uses a cyclic thermal stress model to estimate the cyclic thermal stress, thereby providing insight into the impact of temperature cycling on the device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If temperature cycling operation is performed, then power electronic devices can function and convert power, but thermal stress accumulates causing material fatigue and premature component failure
Solution Approach 1:
The system performs preliminary assessment of thermal stress conditions by extracting thermal cycle data and evaluating it against a cyclic thermal stress model before failure occurs. This allows proactive identification of dangerous operating conditions and enables preventive control actions to be taken, resolving the contradiction by protecting reliability while maintaining productivity.
Solution Approach 2:
The system continuously monitors temperature data, extracts thermal cycle characteristics, evaluates them through the stress model, and provides feedback on the estimated cyclic thermal stress. This feedback loop enables real-time assessment of the tension between power conversion activity and component longevity, allowing dynamic adjustment of operating conditions.
2Loss of information
If thermal cycle data is extracted and evaluated through a cyclic thermal stress model, then insight into thermal stress levels is obtained, but computational complexity increases
Solution Approach 1:
The system extracts only the essential thermal cycle data characteristics needed for stress evaluation from the raw temperature data, rather than processing complete temperature histories. This extraction approach provides necessary thermal stress insight while minimizing computational complexity by focusing only on relevant features.
Solution Approach 2:
The system uses a pre-established cyclic thermal stress model that contains predetermined stress levels for various thermal cycling operating points. Instead of performing complex real-time stress calculations, the system copies or looks up stress information from the pre-computed model based on current operating conditions, reducing computational complexity while maintaining insight quality.
Data Source
AI summary
A method and apparatus for estimating a cyclic thermal stress of a power semiconductor device, the apparatus being configured to receive temperature data indicative of a temperature relating to the power semiconductor device, extract, from the received temperature data, thermal cycle data on characteristic quantities of one or more thermal cycles of the power semiconductor device, determine a thermal cycling operating point of the power semiconductor device on the basis of the extracted thermal cycle data, and determine an estimate of the cyclic thermal stress of the power semiconductor device on the basis of the determined thermal cycling operating point of the power semiconductor device and a cyclic thermal stress model of the power semiconductor device, wherein the cyclic thermal stress model includes data indicative of a stress level of the power semiconductor device at predetermined thermal cycling operating points of the power semiconductor device.