There is an article about On the New Analytical Design of Efficient Inductive Links with Maximum Biomedical Wireless Power Transfer Capability and Area Controllability. Here is what it is about
Key Features of the Study:
Optimal Frequency Identification:
The study identifies the frequency where PTE is maximized without using conventional resonant capacitors.
Design Equations:
The authors derive closed-form equations for optimal inductance and matching network parameters.
Impact of Coil Area:
It analyzes the trade-off between coil area and PTE, exploring how geometry affects efficiency.
Tissue Interaction:
The study incorporates the effects of tissue as a medium on power transfer and adjusts coil parameters accordingly.
Practical Implementation:
A prototype operating at 20 MHz is simulated using tools like Ansys HFSS, demonstrating the proposed design’s effectiveness in a tissue environment.
The goal is to replicate this assignment on python. Here is how….
Replicating the Study in Python:
Here’s a high-level roadmap to replicate the analysis using Python:
The five problem
1. Define Coil Parameters and Formulas:
Use the equations for self-inductance, optimal frequency (fopt), and coupling coefficient (k).
Example: Calculate Lopt using the provided formula.
2. Optimize the Inductive Link:
Implement functions for S-parameters (|S21|, etc.) to evaluate PTE.
Example: Use the formula for |S21| and optimize it to find fopt.
3. Incorporate IMNs:
Model and simulate L-section impedance matching networks using transmission line theory.
Example: Implement matrix calculations for IMN as described.
4. Simulate the Environment:
Simulate the effects of tissue (e.g., resistance and inductance changes) using provided formulas.
5. Visualization and Validation:
Use Python libraries like Matplotlib for plotting PTE vs. frequency or coil area.
Compare results to theoretical expectations or available simulation benchmarks.
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