Date of Award
Master of Science in Biomedical Engineering
Committee Member 1
Committee Member 2
Successful physiological integration of electronics will open the doors to new methods of treatment and diagnoses. One of the key challenges of this integration is designing devices as small as possible while still maintaining high functionality, such as bio-signal recording, processing, telemetry, and stimulation. Wireless power transfer (WPT) can help shrink a device’s footprint by removing the need for bulky batteries. While many modalities of WPT exist for biomedical applications, the optimal power transfer efficiency (PTE) is seldom achieved due to improper impedance matching. Existing methods for determining the optimal impedance matching conditions tend to be application specific and make assumptions incompatible with biomedical applications.
In this work, I present a new formulation of the generalized coupling matrix, a tool typically used for filter synthesis, as a method for optimization of WPT networks. This impedance matching synthesis method can account for non-ideal resonators, weak couplings, complex loads, mixed couplings, and arbitrary sized WPT networks. Moreover, I present a hybrid optimization strategy that combines a genetic algorithm with SQP to generate numerical solutions for optimal impedance matching and user designed power splitting. I demonstrate the validity of the model, as well as the versatility by applying the optimization to both inductor coil and resonant cavity modalities of WPT. This tool shows utility for rapid design of WPT networks and for dynamic tuning control methods.
Thackston, Kyle A., "Optimization of wireless power networks for biomedical applications" (2016). Open Access Theses. 819.