A method for determining design parameters of a silicon carbide switch
By fusing multi-source data and modeling manufacturing deviations, a robust evaluation model is constructed. Robust multi-objective solution and reinforcement learning are then performed to generate a robust parameter window. This addresses the impact of manufacturing deviations in silicon carbide switch design, achieving robustness and coverage of design parameters, and improving design accuracy and engineering applicability.
CN122154433APending Publication Date: 2026-06-05SHENZHEN MULINSHENG MICROELECTRONICS CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHENZHEN MULINSHENG MICROELECTRONICS CO LTD
- Filing Date
- 2026-02-13
- Publication Date
- 2026-06-05
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Figure CN122154433A_ABST
Abstract
The application provides a design parameter determination method of a silicon carbide switch, comprising the following steps: firstly, collecting and processing multi-source data related to the silicon carbide switch, extracting efficiency, stress and reliability evaluation elements, establishing a design parameter space and generating a candidate design parameter set; then, identifying manufacturing deviation factors and constructing a manufacturing deviation description model to form manufacturing deviation constraint conditions corresponding to the candidate design parameter set; further, establishing a robust evaluation model to evaluate the robust performance of the candidate design parameter and form an evaluation record, and updating the evaluation credibility information; on this basis, performing robust multi-objective solving to obtain an initial robust parameter window; subsequently, constructing an active sampling iteration environment, training a sampling decision strategy by using reinforcement learning, and iteratively triggering simulation evaluation and actual measurement evaluation to update the model and gradually shrink the parameter window; when the convergence condition is met, outputting the final robust parameter window as the design parameter determination result.
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