Electromagnetic Metasurface Layout for Wireless Energy Transfer Gain
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing design formulas for electromagnetic metasurfaces in wireless energy transfer systems overlook changes in electromagnetic wave amplitudes due to spatial decay and unit characteristics, leading to suboptimal performance in energy transfer efficiency and gain.
Innovation Solution
An analysis method that treats each metasurface unit as an independent radiator, using the Friis transmission equation and electric field superposition to calculate the superposition of electromagnetic waves, and formulating a quadratic 0-1 integer programming problem to optimize energy transfer efficiency and gain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If simple design formulas are used for metasurface focusing and directional beams, then calculation is simplified, but changes in electromagnetic wave amplitudes due to spatial decay and unit characteristics are overlooked, leading to suboptimal performance
Solution Approach 1:
The metasurface is segmented into M independent unit elements, each treated as a separate radiator. This allows the total electromagnetic field to be calculated as the superposition of fields from each unit, enabling precise accounting of amplitude variations due to spatial decay and unit characteristics while maintaining systematic calculation through modular processing of each segment's contribution
Solution Approach 2:
The invention introduces amplitude coefficients am and bm that explicitly account for spatial decay and unit characteristics, transforming the simple phase-based design formulas into parameter-enriched expressions. These parameters modify the electromagnetic field calculation to include amplitude variations, thereby improving energy transfer efficiency prediction accuracy without excessive computational complexity
2Reliability
If metasurface units are treated as independent radiators with amplitude and phase characteristics, then energy transfer efficiency is improved, but calculation and optimization complexity increases
Solution Approach 1:
The invention enriches the design parameters by introducing amplitude coefficients am and bm alongside phase characteristics. These parameters are integrated into the electromagnetic field superposition formula, allowing precise modeling of each unit's radiation characteristics while maintaining a systematic calculation framework that balances accuracy with computational feasibility
Solution Approach 2:
The invention uses simulation-based channel characteristics Cm that capture the electromagnetic behavior of each unit element. By pre-characterizing each unit's response through simulation and then superposing these characterized responses, the method avoids repeated full-wave simulations during optimization, reducing overall computational complexity while maintaining high accuracy in energy transfer efficiency prediction
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method effectively improves the performance of wireless energy transfer, wireless communication, and simultaneous wireless information and power transfer systems by optimizing metasurface unit arrangement and considering both amplitude and phase characteristics.
Implementation Method 1
Based on the Friis transmission equation and the principle of electric field superposition, this method treats each metasurface unit as an independent radiator
Implementation Method 2
Based on the Friis transmission equation and the principle of electric field superposition, this method treats each metasurface unit as an independent radiator, and calculates the superposition of electromagnetic waves influenced by each unit at a receiver
Data Source
AI summary
An analysis method for evaluating and optimizing wireless energy transfer efficiency and gain of electromagnetic metasurfaces comprises: acquiring total channel characteristics of an mth metasurface unit in a system; acquiring a total channel characteristic matrix C of the metasurface in the system; acquiring a matrix U; acquiring a matrix T; acquiring a quadratic 0-1 integer programming problem for determining the energy transfer efficiency or gain; and using a solution of the above programming problem to obtain optimized energy transfer efficiency or optimized gain, and obtain optimized metasurface unit arrangement. Based on the Friis transmission equation and principle of electric field superposition, this method treats each metasurface unit as an independent radiator, and calculates the superposition of electromagnetic waves influenced by each unit at a receiver or in the far-field of the metasurface, therefore effectively improve the performance of wireless energy transfer, wireless communication, and simultaneous wireless information and power transfer.