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Adaptive Frequency Control of a Sensorless-Receiver Inductive Wireless Power Transfer System Based on Mixed-Compensation Topology

Ahmed Koran, Khaled Badran

2020IEEE Transactions on Power Electronics33 citationsDOI

Abstract

In this article, an adaptive frequency control scheme of a sensorless-receiver inductive wireless power transfer system for battery charging applications is proposed. The mixed-compensation topology is utilized instead of the conventional topologies to deliver power more efficiently. Perturb and observe is proposed to track the optimal operating frequency to achieve maximum transfer efficiency or maximum output power delivery. Moreover, the paper proposes a highly accurate analytical model considering the nonlinear effect of the ac/dc rectifier-stage. Two subsystems are considered: a rectifier based resistive-load, and a rectifier based battery-load. The rectifier based battery-load is represented as a variable ac voltage source. The proposed model is linearized using the first harmonic approximation technique and generalized using the Thévenin's equivalent representation, thus the proposed model can be applied to any compensation topology. Afterward, a systematic approach is developed based on the proposed model to estimate the connected load information including battery voltage based on sender-side measurements only. This results in a smaller size and increased portability of the receiver. A prototype is designed in small-scale with low-power specifications to comply with implantable biomedical applications to demonstrate and validate the proposed model, estimation approach, and frequency tracking experimentally.

Topics & Concepts

Rectifier (neural networks)Wireless power transferMaximum power transfer theoremComputer scienceTopology (electrical circuits)Electronic engineeringCompensation (psychology)Control theory (sociology)HarmonicBattery (electricity)Power (physics)Electrical engineeringEngineeringWirelessTelecommunicationsPhysicsRecurrent neural networkControl (management)PsychoanalysisPsychologyMachine learningQuantum mechanicsStochastic neural networkArtificial neural networkArtificial intelligenceWireless Power Transfer SystemsEnergy Harvesting in Wireless NetworksAdvanced Battery Technologies Research
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