Modeling and Optimization of Kinetic-based Micro Energy-Harvesters for Wearables and Implants

Description

Energy Harvesting is the process of capturing and storing energy from the ambient environment. Kinetic energy harvested from the human body motion is the most convenient and attractive solution for wearable or implantable biomedical sensors in healthcare applications. Increasing functionality and complexity along with the desired miniaturization have drawn the attention of researchers to the limited power source in these devices. Requiring frequent recharge or battery replacement is simply not feasible in many healthcare applications. Therefore, any technology that can prolong the operational lifetime of these devices will undoubtedly contribute toward their increasing commercial adoption. Energy harvesting has the potential to prolong the battery lifetime of these small sensors. In this project, our objective is to develop a computational model of the Coulomb Force Parametric Generator and investigate various strategies that can be used to maximize the output harvested power.

Recent Publications

• M. Roudneshin, K. Sayrafian, A. G. Aghdam, "Maximizing Harvested Energy in Coulomb Force Parametric Generators", IEEE 2022 American Control Conference, Atlanta, Georgia, USA, June 8-10, 2022
• M. Roudneshin, K. Sayrafian, and A. G. Aghdam, “Adaptive Estimation of Near-Optimal Electrostatic Force in Micro Energy-Harvesters”, IEEE Conference on Control Technology and Applications (CCTA), Montreal, Canada, Aug. 24-26, 2020
• M. Roudneshin, K. Sayrafian. A. Aghdam, “A Machine Learning Approach to the Estimation of Near-Optimal Electrostatic Force in Micro Energy-Harvesters”, 7^th Annual IEEE International Conference on Wireless for Space and Extreme Environments (WISEE 2019), Ottawa, Canada, Oct. 16-18, 2019