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Mutual Inductance Estimation of SS-IPT System through Time-Domain Modeling and Nonlinear Least Squares

Liping Mo, Xiaosheng Wang, Yibo Wang, Ben Zhang, Chaoqiang Jiang*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

105 Downloads (CityUHK Scholars)

Abstract

Inductive power transfer (IPT) systems are pivotal in various applications, relying heavily on the accurate estimation of mutual inductance to enable system interoperability discrimination and optimal efficiency tracking control. This paper introduces a novel mutual inductance estimation method for Series-Series IPT (SS-IPT) systems, utilizing time-domain modeling combined with nonlinear least squares. Initially, the time-domain model of SS-IPT systems is developed by deriving its ordinary differential equations (ODEs). Subsequently, the mutual inductance is estimated directly from these ODEs using a nonlinear least-squares approach. This approach necessitates only primary-side information, eliminating the need for communication, supplementary equipment, or frequency scanning. The simplicity and directness of using collected real-time data enhance the practical applicability of our approach. The effectiveness of the proposed method is substantiated through simulations and experimental data. Results demonstrate that the estimation accuracy of our method remains more than 95.0% in simulations and more than 92.5% in experimental data. © 2024 by the authors.
Original languageEnglish
Article number3307
JournalEnergies
Volume17
Issue number13
Online published5 Jul 2024
DOIs
Publication statusPublished - Jul 2024

Funding

This research was funded in part by the Science Technology and Innovation Committee of Shenzhen Municipality, China, grant number SGDX20210823104003034, in part by the Research Grants Council, Hong Kong SAR, grant number C1002-23Y, in part by the Huawei Seed Project Donation, grant number 9229131 and Chow Sang Sang Fund Donation, grant number 9229159. And The APC was funded by the Science Technology and Innovation Committee of Shenzhen Municipality, China, grant number SGDX20210823104003034.

Research Keywords

  • inductive power transfer system
  • nonlinear least square
  • parameter estimation

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

RGC Funding Information

  • RGC-funded

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