Alyssa Zhou

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2020-144

August 12, 2020

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-144.pdf

The proliferation of Internet-of-Things (IoT) systems and human body sensors is rapidly transforming the way we interact with our surroundings. As these devices increase in number and longevity, there grows a critical need to find sustainable and convenient power sources. Shrinking consumer electronics have generated a demand for battery-less power sources for some applications. Significant interest in studying energy harvesting techniques exists as a solution to power these devices. In particular for interactive electronics meant to exist on and around the human body, kinetic energy of human movement is a popular energy scavenging source.

This dissertation presents an electrostatic, charge-pumping energy harvesting system capable of scavenging energy from capacitive changes induced by the human body. As is well known for touchscreen devices, the proximity of a finger alters the effective value of small capacitances. These capacitance changes drive a current which is rectified to charge an energy storage component. This technology is fabricated in a standard CMOS process, and is also compatible with other mediums such as printed circuit boards, conductive fabrics, and paper. These systems transduce the kinetic energy of a human finger tap to electrical energy in the range of pico- to nano- joules, depending on the size, material, and design of the capacitive touch-sensing electrodes. We highlight the harvester's ability to power low-power applications such as light-emitting diodes and ring oscillators. This system illustrates one solution for powering the growing number of electronic devices with on-demand, user-generated interactive human movement.

Advisors: Michel Maharbiz

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BibTeX citation:

@phdthesis{Zhou:EECS-2020-144,
    Author= {Zhou, Alyssa},
    Title= {Charge Pumping with Human Capacitance for Body Energy Harvesting},
    School= {EECS Department, University of California, Berkeley},
    Year= {2020},
    Month= {Aug},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-144.html},
    Number= {UCB/EECS-2020-144},
    Abstract= {The proliferation of Internet-of-Things (IoT) systems and human body sensors is rapidly transforming the way we interact with our surroundings. As these devices increase in number and longevity, there grows a critical need to find sustainable and convenient power sources. Shrinking consumer electronics have generated a demand for battery-less power sources for some applications. Significant interest in studying energy harvesting techniques exists as a solution to power these devices. In particular for interactive electronics meant to exist on and around the human body, kinetic energy of human movement is a popular energy scavenging source. 

This dissertation presents an electrostatic, charge-pumping energy harvesting system capable of scavenging energy from capacitive changes induced by the human body. As is well known for touchscreen devices, the proximity of a finger alters the effective value of small capacitances. These capacitance changes drive a current which is rectified to charge an energy storage component. This technology is fabricated in a standard CMOS process, and is also compatible with other mediums such as printed circuit boards, conductive fabrics, and paper. These systems transduce the kinetic energy of a human finger tap to electrical energy in the range of pico- to nano- joules, depending on the size, material, and design of the capacitive touch-sensing electrodes. We highlight the harvester's ability to power low-power applications such as light-emitting diodes and ring oscillators. This system illustrates one solution for powering the growing number of electronic devices with on-demand, user-generated interactive human movement.},
}

EndNote citation:

%0 Thesis
%A Zhou, Alyssa 
%T Charge Pumping with Human Capacitance for Body Energy Harvesting
%I EECS Department, University of California, Berkeley
%D 2020
%8 August 12
%@ UCB/EECS-2020-144
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-144.html
%F Zhou:EECS-2020-144