Analytical Modeling of Batteryless IoT Sensors Powered by Ambient Energy Harvesting

TL;DR

This paper develops a detailed mathematical model for batteryless IoT sensors powered by ambient energy harvesting, enabling accurate prediction of energy dynamics and device behavior in varying environmental conditions.

Contribution

It introduces a novel comprehensive model that captures energy harvesting and consumption, validated through experiments, to improve power management in batteryless IoT devices.

Findings

Model accurately predicts supercapacitor voltage profiles

Strong correlation between analytical and experimental results

Applicable to diverse environmental conditions

Abstract

This paper presents a comprehensive mathematical model to characterize the energy dynamics of batteryless IoT sensor nodes powered entirely by ambient energy harvesting. The model captures both the energy harvesting and consumption phases, explicitly incorporating power management tasks to enable precise estimation of device behavior across diverse environmental conditions. The proposed model is applicable to a wide range of IoT devices and supports intelligent power management units designed to maximize harvested energy under fluctuating environmental conditions. We validated our model against a prototype batteryless IoT node, conducting experiments under three distinct illumination scenarios. Results show a strong correlation between analytical and measured supercapacitor voltage profiles, confirming the proposed model's accuracy.