An International Journal of Optimization and Control: Theories & Applications (Jun 2020)

A misalignment-adaptive wireless power transfer system using PSO-based frequency tracking

  • Fuat Kilic,
  • Serkan Sezen,
  • Seyit Ahmet Sis

DOI
https://doi.org/10.11121/ijocta.01.2020.00926
Journal volume & issue
Vol. 10, no. 2

Abstract

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One of the major challenges in inductive wireless power transfer (WPT) systems is that the optimal frequency of operation may shift predominantly due to coupling variation as a result of so-called frequency splitting phenomenon. When frequency splitting occurs, two additional resonance frequencies split from the coupler’s resonance frequency. Maximum power levels are observed at these split resonance frequencies; however, these frequencies are strongly-dependent on the coupling coefficient, hence the distance and alignment between the couplers. In addition to that, peak power values at these frequencies can be different from each other due to small impedance differences between the primary and secondary side resonant couplers, forming a local and a global maximum. Therefore, the WPT system should adaptively operate at the correct frequency for achieving maximum power transfer. In this paper, a metaheuristic Particle Swarm Optimization (PSO) based frequency tracking algorithm is proposed for use in WPT systems. The WPT system employs multi sub-coil flux pipe couplers, a full-bridge inverter which is driven by TMS320F28069 controller card and is suitable for high power charging applications. The control algorithm can accurately find the global maximum power point in case of frequency splitting with asymmetric peaks. The proposed frequency tracking algorithm operates only at the primary side based on measurement of the input power level. Therefore, no additional communication link is needed between the primary and the secondary side. Effectiveness of the proposed control method is validated by performing experiments under three different misalignment scenarios and compared to the traditional Perturb and Observe algorithm.

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