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公开(公告)号:US20250102593A1
公开(公告)日:2025-03-27
申请号:US18472684
申请日:2023-09-22
Applicant: STMicroelectronics International N.V.
Inventor: Francesco Rundo , Michele Calabretta , Marco Maria Branciforte , Concetto Spampinato , Salvatore Coffa
Abstract: A method of characterizing a parameter (e.g., threshold voltage) of a power electronic device using an artificial intelligence (AI) model includes sampling measured parameter values (e.g., voltage, current) of the power electronic device during operation and characterizing the parameter of the power electronic device using the AI model in inference mode with the measured parameter values as inputs. The AI model is trained using a joint loss function including a Jacobian regularization term. The Jacobian regularization term may depend on the norm of at least one Jacobian of a corresponding set of training inputs. A power electronics system configured to perform the method includes the power electronic device and a computing system with a processor and memory storing the AI model. The computing system may be a microcontroller. The system may also include an analog-to-digital converter (ADC) circuit, such as in the microcontroller.
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公开(公告)号:US20250020710A1
公开(公告)日:2025-01-16
申请号:US18349791
申请日:2023-07-10
Applicant: STMicroelectronics International N.V.
Inventor: Francesco Rundo , Carmelo Pino , Michele Calabretta , Alessandro Sitta , Angelo Alberto Messina , Salvatore Coffa
IPC: G01R31/26
Abstract: A method for monitoring voltage drift includes measuring a voltage across a diode of a power device, providing the measured voltage as an input to a controller, the controller being configured to run a transformer-based model, and forecasting a range of expected future values of the voltage across the diode of the power device with the transformer-based model. The transformer-based model may include a temporal fusion transformer with a temporal convolutional neural network and an adversarial compensation model with a backpropagation algorithm.
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