Please use this identifier to cite or link to this item: http://theses.ncl.ac.uk/jspui/handle/10443/5035
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dc.contributor.authorGao, Kaiyuan-
dc.date.accessioned2021-09-14T09:39:43Z-
dc.date.available2021-09-14T09:39:43Z-
dc.date.issued2020-
dc.identifier.urihttp://theses.ncl.ac.uk/jspui/handle/10443/5035-
dc.descriptionPhD Thesisen_US
dc.description.abstractWith the rapid advancement of electronic and mechanical system miniaturisation, new application types such as portable systems, internet of things (IoT) and wireless sensor networks (WSNs) have become promising areas of growth for industry. In these areas, the limits on battery life have opened opportunities for energy harvesting to become a commonplace choice as the system power source, which brings its own problems. One of these problems is that energy harvesting is in general a much more variable energy source than batteries and mains power supply, because of the unpredictable and intermittent nature of the external energy environment [1]. This implies that both energy harvesters and the loads they support require significantly more control, tuning and management than if the energy was supplied by traditional means. On the other hand, sensing is also an important aspect for such systems as many of these systems are sensors used to monitor physical parameters in the environment. Another reason is that the control, tuning and management of energy harvesting requires the support of energy/power sensing. It is therefore inevitable that sensing methods need to be developed targeting an environment where energy supply is volatile. However, sensing under a variable energy supply faces numerous problems. One such problem is the energy consumption of the sensing itself. In this regard, the capacitive sensor is widely used for sensing a physical parameter, such as pressure, position, and humidity, as it is suitable for low-power applications with limited energy budgets [2–4]. Another problem faced by sensing under energy supply variability is the difficulty of maintaining stable voltage and/or current references. This thesis is motivated by these issues. In this thesis, a new sensing method is developed based on time domain techniques, which will be shown to be 1) suitable for capacitive sensing of environmental physical parameters, 2) suitable for sensing voltage, from which power and energy information can be derived, supporting energy harvesting management uses, and 3) robust to voltage and power volatility, making sensors derived from this method useful for miniaturised and energy autonomous systems. At the centre of this work is a novel reference-free voltage level-crossing sensor, realised through time comparison techniques. By working in the time domain, it avoids the need for voltage or current references. Two more sophisticated sensors are then developed around this level-crossing sensing engine. The first is a voltage monitor which is capable of sensing the crossing of multiple predefined voltage boundaries within a range, targeting energy harvesting system management uses. The second is a capacitance-to-digital converter which senses and converts the value of a target capacitance to digital value. This could be used to support the monitoring of physical vi parameters in the environment including pressure, temperature, moisture, etc. as these might be made to directly affect the values of capacitances. This thesis describes detailed design theory and reasoning, implementation, and validation of the presented sensors. Circuits are implemented in very-large-scale integration and investigated in the Cadence Analog Design Environment. In addition to analogue simulations, experiments were also conducted on a fabricated chip. Data collected from these simulation and physical experiments show that the time-domain method developed in this work has quantitative and qualitative advantages over existing designs.en_US
dc.language.isoenen_US
dc.publisherNewcastle Universityen_US
dc.titleVoltage and capacitance sensing using time comparisonen_US
dc.typeThesisen_US
Appears in Collections:School of Engineering

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