Autonomous Energy Harvesting and Power Management Unit for Wireless IoT Applications
Abstract
Internet-of-Things has aroused wide focus to make our society more intelligent and more efficient by employing tremendous connected devices. To ensure its efficiency, battery replacement and maintenance become major challenges. Therefore, energy harvesting (EH) with smart power management is one of the key enabling technologies. With EH technologies, the sensors can autonomously capture the available ambient energy and thus a battery-less solution is even feasible because of the ultra-low-power design techniques.
This dissertation focuses on the EH technologies with smart power management unit (PMU)
and integrated circuits (IC) for Internet-of-Things (IoT) applications. In the first part, three different RF-EH systems for wide input-power range operations are presented with different working scenarios: the first one works with a cascading DC-DC converter for maximum power point tracking (MPPT) and a novel fractional open-circuit voltage approximation (FOCVA) is proposed to help with MPPT; the second one delivers the energy directly to a system-on-chip (SoC) loading with a fully integrated hill-climbing MPPT; the third one employs dual-band operations and a nano-watt hysteresis-controlled switched-capacitor (SC) converter to boost up the output voltage and reduce the reverse leakage current for modulated signal harvesting.
In the second part, an EH system based on autonomous IC interface is proposed to extract
the energy from a centimeter-scale electromagnetic (EM) wind turbine. To improve the efficiency of such an EH system, a self-start-up and self-biased active rectifier is employed. A hysteresis-controlled boost converter is designed with self-zero-current-switching calibrations, which achieves a peak DC-DC efficiency of 93:3% with a maximum efficiency improvement of 12:7%. Also, a novel frequency-to-amplitude conversion (FAC) maximum power point tracking (MPPT) method is proposed for cycle-to-cycle MPPT. In wind-field testing, the EH system starts to track the MPP one cycle after start-up. In the steady-state, the EH system maintains its cycle-to-cycle MPP in different wind speed conditions from 1:0 to 5:0 m/s, achieving a 630% energy extraction gain at a low wind speed of 1:2 m/s.
Citation
Zeng, Zizhen (2020). Autonomous Energy Harvesting and Power Management Unit for Wireless IoT Applications. Doctoral dissertation, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /192832.