A Neural Network Model for Maximum Power Estimation in Dual-Input Phase-Shifted LLC Converter

Abstract

This paper proposes a neural network model for the output power as a function of switching frequency of a dual-input phase-shifted LLC converter. The proposed model can be used to allow fast and efficient maximum power point tracking of the converter. Derivation of the model followed by verification are presented.