Finite‑control‑set model predictive control for magnetically coupled wireless power transfer systems

Chen Qi; Zhengying Lang; Tao Li; Xiyou Chen

Finite‑control‑set model predictive control for magnetically coupled wireless power transfer systems

Vol. 21, No. 7, pp. 1095-1105, Jul. 2021

10.1007/s43236-021-00252-6

wireless power transfer

Model predictive control

Pulse density modulation

Soft switching

Dynamic response

Abstract

Output voltage control is an important subject in magnetically coupled wireless power transfer (MC-WPT) applications. Conventional control methods for MC-WPT systems use the PI controller. However, this method suffers from three issues: time-consuming tuning work of the PI parameters, increased control complexity due to the needs of the modulator, and poor dynamic performance. To provide an attractive alternative to the PI controller, a novel output voltage regulation method based on finite-control-set model predictive control (FCS-MPC) has been proposed for a MC-WPT system. The proposed method has inherent advantages such as a very intuitive concept, no need for a modulator, and fast dynamic response. Moreover, it can achieve soft switching by constructing pulse-density-modulation-based voltage pulse sequences as the control set. The design and implementation of the proposed controller are discussed in this paper. The proposed control method has been tested on a series-series-compensated MC-WPT system, and experimental results demonstrate the effectiveness of the proposed control method in comparison with PI control methods.

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Cite this article

[IEEE Style]

C. Qi, Z. Lang, T. Li, X. Chen, "Finite‑control‑set model predictive control for magnetically coupled wireless power transfer systems," Journal of Power Electronics, vol. 21, no. 7, pp. 1095-1105, 2021. DOI: 10.1007/s43236-021-00252-6.

[ACM Style]

Chen Qi, Zhengying Lang, Tao Li, and Xiyou Chen. 2021. Finite‑control‑set model predictive control for magnetically coupled wireless power transfer systems. Journal of Power Electronics, 21, 7, (2021), 1095-1105. DOI: 10.1007/s43236-021-00252-6.