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Doctoral thesis
License: CC BY
Data sources: UnpayWall
https://doi.org/10.18130/v3mk7...
Doctoral thesis . 2016 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.18130/v3...
Doctoral thesis . 2016
Data sources: Datacite
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Energy Harvesting System Modeling

Energy Harvesting System Modeling

Abstract

DC-DC converters are electrical circuits that transfer energy from a DC voltage source to a load and regulate the output voltage. These circuits are widely used in energy harvesting applications, and should be optimized based on input power and load requirements to have maximum converter efficiency. SPICE is one of the popular tools used for this purpose which requires the user to design a circuit in the tool and perform the optimization. This requires a significant amount of time of the user at the design stage. This thesis develops a tool based on MATLAB Simulink to carry out the preliminary analysis of a power management circuits in an energy harvesting system. The tool consists of models on two inductor based DC-DC converters, linear dropout regulator (LDO) and five different non inductor based DC-DC converters. Individual models were verified in SPICE using 130 nm CMOS technology. The model is further developed to make a unified global energy harvesting model for inductor based and non inductor based DC-DC converters. The usage of a unified model for energy harvesting systems is presented in detail using three experiments. The tool can accurately model the functionality, energy and efficiency of the functional components of energy scavenging systems. This modeling can be used to make architectural design decisions in a power management unit in system-on-chip applications.

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Keywords

DC-DC converter modeling, Simulink, Energy harvesting modeling, SOC

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid
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