Genetic algorithm based geometry optimization of inductively coupled printed spiral coils for remote powering of electronic implantable devices

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.