Energy harvesting system design and optimization for wireless sensor networks

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dc.contributor.advisorÓ Mathúna, S. Cianen
dc.contributor.advisorWang, Ningningen
dc.contributor.authorWang, Wensi S.
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2014-02-24T15:54:44Z
dc.date.available2014-02-24T15:54:44Z
dc.date.issued2014
dc.date.submitted2014
dc.description.abstractWireless sensor networks (WSN) are becoming widely adopted for many applications including complicated tasks like building energy management. However, one major concern for WSN technologies is the short lifetime and high maintenance cost due to the limited battery energy. One of the solutions is to scavenge ambient energy, which is then rectified to power the WSN. The objective of this thesis was to investigate the feasibility of an ultra-low energy consumption power management system suitable for harvesting sub-mW photovoltaic and thermoelectric energy to power WSNs. To achieve this goal, energy harvesting system architectures have been analyzed. Detailed analysis of energy storage units (ESU) have led to an innovative ESU solution for the target applications. Battery-less, long-lifetime ESU and its associated power management circuitry, including fast-charge circuit, self-start circuit, output voltage regulation circuit and hybrid ESU, using a combination of super-capacitor and thin film battery, were developed to achieve continuous operation of energy harvester. Low start-up voltage DC/DC converters have been developed for 1mW level thermoelectric energy harvesting. The novel method of altering thermoelectric generator (TEG) configuration in order to match impedance has been verified in this work. Novel maximum power point tracking (MPPT) circuits, exploring the fractional open circuit voltage method, were particularly developed to suit the sub-1mW photovoltaic energy harvesting applications. The MPPT energy model has been developed and verified against both SPICE simulation and implemented prototypes. Both indoor light and thermoelectric energy harvesting methods proposed in this thesis have been implemented into prototype devices. The improved indoor light energy harvester prototype demonstrates 81% MPPT conversion efficiency with 0.5mW input power. This important improvement makes light energy harvesting from small energy sources (i.e. credit card size solar panel in 500lux indoor lighting conditions) a feasible approach. The 50mm × 54mm thermoelectric energy harvester prototype generates 0.95mW when placed on a 60oC heat source with 28% conversion efficiency. Both prototypes can be used to continuously power WSN for building energy management applications in typical office building environment. In addition to the hardware development, a comprehensive system energy model has been developed. This system energy model not only can be used to predict the available and consumed energy based on real-world ambient conditions, but also can be employed to optimize the system design and configuration. This energy model has been verified by indoor photovoltaic energy harvesting system prototypes in long-term deployed experiments.en
dc.description.sponsorshipScience Foundation Ireland (ITOBO Project (06-SRC-I1091))en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Version
dc.format.mimetypeapplication/pdfen
dc.identifier.citationWang, W. 2014. Energy harvesting system design and optimization for wireless sensor networks. PhD Thesis, University College Cork.en
dc.identifier.endpage193
dc.identifier.urihttps://hdl.handle.net/10468/1410
dc.language.isoenen
dc.publisherUniversity College Corken
dc.rights© 2014, Wensi Wang.en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/en
dc.subjectEnergy harvestingen
dc.subjectDC-DC converteren
dc.subjectMaximum power point trackingen
dc.subject.lcshDC-to-DC convertersen
dc.subject.lcshWireless sensor networksen
dc.subject.lcshSupercapacitorsen
dc.thesis.opt-outfalse
dc.titleEnergy harvesting system design and optimization for wireless sensor networksen
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePHD (Engineering)en
ucc.workflow.supervisorcian.omathuna@tyndall.ie
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