AI Summary & Key Takeaways
AI InsightEffectiveness of theproposed control method is validated by performing experiments under threedifferent misalignment scenarios and compared to the traditional Perturb andObserve algorithm.
📌 3 Key Takeaways
Abstract
One of the major challenges in inductive wireless power transfer (WPT) systemsis that the optimal frequency of operation may shift predominantly due to couplingvariation as a result of so-called frequency splitting phenomenon. When frequencysplitting occurs, two additional resonance frequencies split from the coupler’sresonance frequency. Maximum power levels are observed at these split resonancefrequencies; however, these frequencies are strongly-dependent on the couplingcoefficient, hence the distance and alignment between the couplers. In addition tothat, peak power values at these frequencies can be different from each other dueto small impedance differences between the primary and secondary side resonantcouplers, forming a local and a global maximum. Therefore, the WPT systemshould adaptively operate at the correct frequency for achieving maximum powertransfer. In this paper, a metaheuristic Particle Swarm Optimization (PSO) basedfrequency tracking algorithm is proposed for use in WPT systems. The WPTsystem employs multi sub-coil flux pipe couplers, a full-bridge inverter which isdriven by TMS320F28069 controller card and is suitable for high power chargingapplications. The control algorithm can accurately find the global maximum powerpoint in case of frequency splitting with asymmetric peaks. The proposedfrequency tracking algorithm operates only at the primary side based onmeasurement of the input power level. Therefore, no additional communicationlink is needed between the primary and the secondary side. Effectiveness of theproposed control method is validated by performing experiments under threedifferent misalignment scenarios and compared to the traditional Perturb andObserve algorithm.