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Title: Power processing for electrostatic microgenerators
Author: Gandu, Kondalarao
ISNI:       0000 0004 2705 1131
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2011
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Microgenerators are electro-mechanical devices which harvest energy from local environmental from such sources as light, heat and vibrations. These devices are used to extend the life-time of wireless sensor network nodes. Vibration-based microgenerators for biomedical applications are investigated in this thesis. In order to optimise the microgenerator system design, a combined electro-mechanical system simulation model of the complete system is required. In this work, a simulation toolkit (known as ICES) has been developed utilising SPICE. The objective is to accurately model end-to-end microgenerator systems. Case-study simulations of electromagnetic and electrostatic microgenerator systems are presented to verify the operation of the toolkit models. Custom semiconductor devices, previously designed for microgenerator use, have also been modelled so that system design and optimisation of complete microgenerator can be accomplished. An analytical framework has been developed to estimate the maximum system effectiveness of an electrostatic microgenerator operating in constant-charge and constant-voltage modes. The calculated system effectiveness values are plotted with respect to microgenerator sizes for different input excitations. Trends in effectiveness are identified and discussed in detail. It was found that when the electrostatic transducer is interfaced with power processing circuit, the parasitic elements of the circuit are reducing the energy generation ability of the transducer by sharing the charge during separation of the capacitor plates. Also, found that in constant-voltage mode the electrostatic microgenerator has a better effectiveness over a large operating range than constant-charge devices. The ICES toolkit was used to perform time-domain simulation of a range of operating points and the simulation results provide verification of the analytical results.
Supervisor: Mitcheson, Paul ; Green, Tim Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral