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Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
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Related Experiment Video

Updated: Jul 4, 2026

Optimization of An Air-Based Heat Management System for Dusty Particulate Matter-Covered Lithium-Ion Battery Packs
10:36

Optimization of An Air-Based Heat Management System for Dusty Particulate Matter-Covered Lithium-Ion Battery Packs

Published on: November 3, 2023

Joint power-time resource optimization for multi-tag RFID wireless power transfer via model predictive control and

Lina Yuan1, Xiaoye Wang2, Huajun Chen1

  • 1School of Data Science, Tongren University, Tongren, China.

Plos One
|May 4, 2026
PubMed
Summary

This study introduces a Joint Power-Time Optimization (JPTO) framework for long-range wireless power transfer (WPT) systems. The new approach enhances energy efficiency and ensures fairness for multiple Internet of Things (IoT) tags.

Related Experiment Videos

Last Updated: Jul 4, 2026

Optimization of An Air-Based Heat Management System for Dusty Particulate Matter-Covered Lithium-Ion Battery Packs
10:36

Optimization of An Air-Based Heat Management System for Dusty Particulate Matter-Covered Lithium-Ion Battery Packs

Published on: November 3, 2023

Area of Science:

  • Wireless Power Transfer (WPT)
  • Internet of Things (IoT)
  • Radio Frequency Identification (RFID)

Background:

  • Conventional wireless power transfer systems often use fixed-parameter controllers, leading to suboptimal energy efficiency and fairness.
  • Existing systems struggle to adapt to time-varying channel conditions and heterogeneous device requirements in IoT networks.
  • Reactive Proportional-Integral-Derivative (PID) controllers lack the adaptability needed for dynamic WPT environments.

Purpose of the Study:

  • To develop a comprehensive optimization framework for long-range RFID-based WPT systems.
  • To maximize end-to-end energy efficiency while ensuring Quality-of-Service (QoS) fairness among multiple IoT tags.
  • To introduce adaptive control and resource allocation strategies for improved WPT performance.

Main Methods:

  • Implemented a Model Predictive Control (MPC)-based adaptive power control mechanism to replace traditional PID controllers.
  • Developed a convex optimization framework for dynamic Time-Division Multiple Access (TDMA) slot allocation to ensure energy harvesting fairness.
  • Utilized an Alternating Direction Method of Multipliers (ADMM)-based distributed algorithm to solve the non-convex joint optimization problem.

Main Results:

  • The proposed Joint Power-Time Optimization (JPTO) framework achieved a peak efficiency of 37.6%, significantly outperforming conventional PID control (28.4%).
  • Demonstrated a 61.9% reduction in power fluctuations, leading to more stable power delivery.
  • Maintained a normalized fairness index of 0.94 for heterogeneous IoT loads (sensors) across distances of 0.5-5 meters.

Conclusions:

  • The JPTO framework effectively optimizes long-range RFID-based WPT systems for enhanced energy efficiency and fairness.
  • The adaptive MPC and distributed ADMM algorithms provide robust solutions for dynamic and complex IoT environments.
  • The proposed system is validated for diverse mobile IoT applications requiring reliable wireless power delivery.