Infineon Technologies Austria Ag

Sandro Cerato

Benjamin L Schwabe

Jens A Ejury

Sergio Rossi

Kurt Marquardt

Salman Nazir

A power conversion regulator circuit comprises a regulator input dynamically supplied with a feedback signal representative of an output parameter of a power converter circuit, a regulator output configured to provide a control signal to the power converter circuit, for making adjustments to the output of the power converter circuit, and regulator circuitry configured to generate the control signal for outputting via the regulator output, based on the error signal. The circuit further comprises a processing circuit configured to (a) implement an artificial neural network comprising a plurality of artificial neurons, where the artificial neural network is configured to compute a machine-learning-based (ML-based) prediction of the output parameter, based on the feedback signal, and (b) generate the error signal based at least in part on the ML-based prediction of the output parameter and based on a target level for the output parameter.

AI based error prediction for power conversion regulators

A multiphase power converter comprises a regulator, a value-supply system arranged for collecting at least one operating point of the power converter, and a predictor for determining updated phase statuses, for activating or deactivating each of the phases (, . . . ) during a further operation of the power converter. The updated phase statuses are determined using a process based on the at least one collected operating point and predictor parameters obtained from a machine-learning process.

Multiphase power converter

A power converter comprises a regulator, a value-supply system arranged for collecting at least one operating point of the power converter, and a predictor operative to produce updated regulator parameters (such as one or more power supply coefficients) implemented by the regulator to produce an output voltage to power a load. The updated regulator parameters are determined using a process based on the at least one collected operating point samples and predictor parameters obtained from a machine-learning process.

Electrical power converter

Electrical power converter with predictor

A load control arrangement includes a communication channel configured to transmit information. A controller unit is coupled to the communication channel and configured to at least one of send and receive information via the communication channel. A load control device is coupled to the communication channel, comprising a disconnect switch configured to be coupled to a power line. The load control device is further configured to determine a power consumption of a load connected to the power line. The load control device provides measurement data representing the determined power consumption via the communication channel to the controller unit. The load control device drives the disconnect switch depending on drive information received via the communication channel or depending on the determined power consumption.

Active monitoring and controlling of home loads

An electric power meter arrangement, includes a metrology unit configured to be coupled to a power line and to determine power consumption and provide measurement data representing the power consumption. A programmable control unit including a memory is configured to store software configured to run on the control unit. A security unit is configured to store at least one key and to validate that software stored in the memory of the programmable control unit is authorized.

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Taufkirchen, Germany

Sandro Cerato