Infineon Technologies Austria Ag

Infineon Technologies Ag

Benjamin L Schwabe

Sandro Cerato

Salman Nazir

Jens A Ejury

Christian Rainer

Darryl Galipeau

David Williams

Bernhard Fehr

A method and apparatus for estimating stress on capacitor is provided. A power converter may include an input terminal for receiving an input voltage, a power stage coupled to the input terminal, a capacitor coupled to the power stage, a controller configured to control the power stage to generate an output voltage at the capacitor as a function of the input voltage, and a stress monitor module. The stress monitor module is configured to determine a stress energy metric for the capacitor based on variations in the output voltage and identify a first fault condition based on the stress energy metric.

Method and apparatus for estimating stress on capacitor

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

An electric switch-mode power converter comprises: a parameter predictor for predicting and updating at least one regulator parameter of a regulator controlling a switching device of the converter, a performance feedback signal generator for providing a performance feedback signal indicative of a performance of the conversion operation, wherein the parameter predictor is configured to predict an update of the regulator parameter based on the performance feedback signal and during update intervals, the intervals being during the power conversion operation and being separated by pauses without update.

Electric power converter

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 supply system comprises: a switched-capacitor converter, a controller, and a monitor. Via generation of control signals, the controller controls settings of switches in the switched-capacitor converter to convert a received input voltage to an output voltage that powers a load. The monitor in the power supply system at least occasionally determines an impedance associated with the switched-capacitor converter. A magnitude of the determined impedance provides an indication whether the switched-capacitor converter is operating efficiently. To ensure efficient operation of the switched-capacitor converter, based on input form the monitor, the controller adjusts the control signals controlling the switches in the switched-capacitor converter as a function of the determined impedance.

Adaptive control of a switched voltage converter

A machine learning (ML)-based phase current balancer for a multiphase power converter includes one or more inputs, one or more outputs, and an artificial neural network. The artificial neural network includes a plurality of artificial neurons and is trained to provide corrective phase current imbalance information at the one or more outputs for correcting phase current imbalance within the multiphase power converter, based on information available at the one or more inputs and indicative of individual phase currents of the multiphase power converter.

ML-based phase current balancer

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

An apparatus comprises a passive RFID tag designed to provide information identifying at least one fuel compatible with a vehicle.

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Munich, Germany

Benjamin L Schwabe