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Energy-aware Approaches for Energy Harvesting Powered Wireless Sensor Systems
Date: 9 March 2020
University of Exeter
Doctor of Philosophy in Engineering
Energy harvesting (EH) powered wireless sensor systems (WSSs) are gaining increasing popularity since they enable the system to be self-powering, long-lasting, almost maintenance-free, and environmentally friendly. However, the mismatch between energy generated by harvesters and energy demanded by WSS to perform the required tasks is ...
Energy harvesting (EH) powered wireless sensor systems (WSSs) are gaining increasing popularity since they enable the system to be self-powering, long-lasting, almost maintenance-free, and environmentally friendly. However, the mismatch between energy generated by harvesters and energy demanded by WSS to perform the required tasks is always a bottleneck as the ambient environmental energy is limited, and the WSS is power hunger. Therefore, the thesis has proposed, designed, implemented, and tested the energy-aware approaches for wireless sensor motes (WSMs) and wireless sensor networks (WSNs), including hardware energy-aware interface (EAI), software EAI, sensing EAI and network energy-aware approaches to address this mismatch. The main contributions of this thesis to the research community are designing the energy-aware approaches for EH Powered WSMs and WSNs which enables a >30 times reduction in sleep power consumption of WSNs for successful EH powering WSNs without a start-up issue in the condition of mismatch between the energy generated by harvesters and energy demanded by WSSs in both mote and network systems. For EH powered WSM systems, the energy-aware approaches have (1) enabled the harvested energy to be accumulated in energy storage devices to deal with the mismatch for the operation of the WSMs without the start-up issue, (2) enabled a commercial available WSMs with a reduced sleep current from 28.3 μA to 0.95 μA for the developed WSM, (3) thus enabled the WSM operations for a long active time of about 1.15 s in every 7.79 s to sample and transmit a large number of data (e.g., 388 bytes), rather than a few ten milliseconds and a few bytes. For EH powered WSN systems, on top of energy-aware approached for EH powered WSM, the network energy-aware approaches have presented additional capabilities for network joining process for energy-saving and enabled EH powered WSNs. Once the EH powered WSM with the network energy-aware approach is powered up and began the network joining process, energy, as an example of 48.23 mJ for a tested case, has been saved in the case of the attempt to join the network unsuccessfully. Once the EH-WSM has joined the network successfully, the smart programme applications that incorporate the software EAI, sensing EAI and hardware EAI allow the EH powered WSM to achieve (4) asynchronous operation or (5) synchronised operation based on the energy available after the WSM has joined the network.Through designs, implementations, and analyses, it has been shown that the developed energy-aware approaches have provided an enabled capability for EH successfully powering WSS technologies in the condition of energy mismatch, and it has the potential to be used for wide industrial applications.
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