Capacity Over Capacitance for Reliable Energy Harvesting Sensors

Today, most sensors that harvest energy from indoor solar, ambient RF, or thermal gradients buffer small amounts of energy in capacitors as they intermittently work through a sensing task. While the utilization of capacitors for energy storage affords these systems indefinite lifetimes, their low energy capacity necessitates complex intermittent programming models for state retention and energy management. However, recent advances in battery technology lead us to reevaluate the impact that increased energy storage capacity may have on the necessity of these programming models and the reliability of energy harvesting sensors. In this paper, we propose a capacity-based framework to help structure energy harvesting sensor design, analyze the impact of capacity on key reliability metrics using a data-driven simulation, and consider how backup energy storage alters the design space. We find that for many designs that utilize solar energy harvesting, increasing energy storage capacity to 1-10 mWh can obviate the need for intermittent programming techniques, augment the total harvested energy by 1.4-2.3x, and improve the availability of a sensor by 1.3-2.6x. We also show that a hybrid design using energy harvesting with a secondary-cell battery and a backup primary-cell battery can achieve 2-4x the lifetime of primary-cell only designs while eliminating the failure modes present in energy harvesting systems. Finally, we implement an indoor, solar energy harvesting sensor based on our analysis and find that its behavior aligns with our simulation's predictions.