DEA-based on optimization of inductive coupling for powering implantable biomedical devices

Abstract

Inductive coupling wireless power transfer (WPT) is one of the best technologies for powering implantable microelectronic devices (IMD). A wireless power transfer system’s important elements (indicators) are power transfer efficiency (PTE) and power delivered to load (PDL). The key characteristics of WPT are the size of the transmitting (Tx) and receiving (Rx) coils, the operating frequency, and the separation distance between the two parts of the system. The main goal of this research is to use the differential evolution algorithm (DEA) to optimize a wireless energy transfer system in order to maximize the PTE and PDL. By comparing the results acquired by the proposed technique to those obtained by other methodologies, we were able to validate the results obtained by the suggested method. With the aim of raising the PTE and PDL. Using this metaheuristic approach, we were able to improve WPT’s critical parameters. For is, a PTE of 95% and 136 mW of power delivered to the load for a 13 cm separation distance.

Design and miniaturization of a microsystem to power biomedical implants using grey wolf optimizer-based cuckoo search algorithm

“…based on the best geometric qualities of the WPT's essential element. The GWO-CS algorithm is described in depth in this section, and it is applied to our optimization problem [20], [21].…”