Electronic biomedical implantable sensors need power to perform. Among the main reported approaches, inductive link is the most commonly used method for remote powering of such devices. Power efficiency is the most important characteristic to be considered when designing inductive links to transfer energy to implantable biomedical sensors. The maximum power efficiency is obtained for maximum coupling and quality factors of the coils and is generally limited as the coupling between the inductors is usually very small. This paper is dealing with geometry optimization of inductively coupled printed spiral coils for powering a given implantable sensor system. For this aim, Iterative Procedure (IP) and Genetic Algorithm (GA) analytic based optimization approaches are proposed. Both of these approaches implement simple mathematical models that approximate the coil parameters and the link efficiency values. Using numerical simulations based on Finite Element Method (FEM) and with experimental validation, the proposed analytic approaches are shown to have improved accurate performance results in comparison with the obtained performance of a reference design case. The analytical GA and IP optimization methods are also compared to a purely Finite Element Method based on numerical optimization approach (GA-FEM). Numerical and experimental validations confirmed the accuracy and the effectiveness of the analytical optimization approaches to design the optimal coil geometries for the best values of efficiency.

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Electronic biomedical implantable devices need powering to perform. Among the main reported approaches, inductive links are the most commonly used method for remote powering of such devices. Power efficiency is the most important characteristic to be considered when designing inductive links to transfer energy to implantable devices. The maximum power efficiency is obtained for maximum coupling and quality factors of the coils and is generally limited as the coupling between the inductors is usually very small. This paper is dealing with geometry optimization of inductively coupled printed spiral coils for the powering of a given implant system. For this aim, simple mathematical models that approximate coil parameters and link efficiency are derived, and using these models two different approaches are used to provide optimal coil geometries for a maximum efficiency of the link. First an iterative design procedure is implemented then genetic based algorithm optimisation is derived to find the optimal coil geometries of the used coil structure. Theoretical results are verified by simulation using HFSS software. A comparative analysis confirmed the effectiveness of the genetic algorithm based approach to provide the optimal coil geometries.

This work aims for the design of printed spiral coils (PSC) with high quality factors. This consists in minimizing coil losses represented by proximity and eddy currents losses. For this purpose, specific geometric parameters characterizing spiral coils are shown to have a direct impact on increasing such losses. As a result, to minimize proximity effect, high ratios between the interspace separating two adjacent traces and the trace width are recommended to be used. In addition, to reduce eddy current losses, an empirical equation is developed to determine the optimal inner diameter sizes of the coils. The obtained numerical results confirmed that, using the proposed design constraints, the quality factor of the coils improves by 40 % in average with only 12 % decrease of the coil inductance value. Analytical formulation of the coil quality factor is obtained. Comparing analytical to simulation results, the obtained errors are reduced from 43 % to only 5 % when the recommended design constraints are applied.