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    A new analytical model significantly speeds up the design of inductive charging systems for medical devices. This computational tool enables faster optimization of charging speed and specific absorption rate (SAR) while maintaining accuracy.

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    Area of Science:

    • Biomedical Engineering
    • Electromagnetics
    • Computational Modeling

    Background:

    • Designing wireless charging for implanted medical devices involves balancing competing factors like charging speed, specific absorption rate (SAR), and coil size.
    • Fast electromagnetic solvers are crucial for multi-criteria optimization in these systems.

    Purpose of the Study:

    • To present a novel analytical model based on the quasi-static approximation for optimizing inductive charging systems.
    • To validate the model's speed and accuracy against full-wave simulations and experimental measurements.

    Main Methods:

    • Developed an analytical model using the quasi-static approximation.
    • Benchmarked the model against full-wave simulations for accuracy and computation time.
    • Measured coupling factor and specific absorption rate (SAR) experimentally using test coils and a PAA phantom.

    Main Results:

    • The approximate model achieved a 16% increase in charging speed through multi-criterion optimization.
    • Computation time was drastically reduced: 11 seconds for the approximate model versus 5 hours for full-wave simulations.
    • The model demonstrated high accuracy, with a maximum difference of less than 24% and a mean difference of less than 2% compared to full-wave simulations.

    Conclusions:

    • The proposed approximate model serves as an effective rapid prototyping tool for optimizing wireless charging systems.
    • It enables fast and accurate computation of coupling factor and SAR near conducting structures, facilitating charging speed optimization.