Design, analysis and implementation of voltage sensor for power-constrained systems

PhD ThesisThanks to an extensive effort by the global research community, the electronic technology has significantly matured over the last decade. This technology has enabled certain operations which humans could not otherwise easily perform. For instance, electronic systems can be used to perform sensing, monitoring and even control operations in environments such as outer space, underground, under the sea or even inside the human body. The main difficulty for electronics operating in these environments is access to a reliable and permanent source of energy. Using batteries as the immediate solution for this problem has helped to provide energy for limited periods of time; however, regular maintenance and replacement are required. Consequently, battery solutions fail wherever replacing them is not possible or operation for long periods is needed. For such cases, researchers have proposed harvesting ambient energy and converting it into an electrical form. An important issue with energy harvesters is that their operation and output power depend critically on the amount of energy they receive and because ambient energy often tends to be sporadic in nature, energy harvesters cannot produce stable or fixed levels of power all of the time. Therefore, electronic devices powered in this way must be capable of adapting their operation to the energy status of the harvester. To achieve this, information on the energy available for use is needed. This can be provided by a sensor capable of measuring voltage. However, stable and fixed voltage and time references are a prerequisite of most traditional voltage measurement devices, but these generally do not exist in energy harvesting environments. A further challenge is that such a sensor also needs to be powered by the energy harvester’s unstable voltage. In this thesis, the design of a reference-free voltage sensor, which can operate with a varying voltage source, is provided based on the capture of a portion of the total energy which is directly related to II the energy being sensed. This energy is then used to power a computation which quantifies captured energy over time, with the information directly generated as digital code. The sensor was fabricated in the 180 nm technology node and successfully tested by performing voltage measurements over the range 1.8 V to 0.8 V

A Capacitance-To-Digital Converter for MEMS Sensors for Smart Applications

The use of MEMS sensors has been increasing in recent years. To cover all the applications, many different readout circuits are needed. To reduce the cost and time to market, a generic capacitance-to-digital converter (CDC) seems to be the logical next step. This work presents a configurable CDC designed for capacitive MEMS sensors. The sensor is built with a bridge of MEMS, where some of them function with pressure. Then, the capacitive to digital conversion is realized using two steps. First, a switched-capacitor (SC) preamplifier is used to make the capacitive to voltage (C-V) conversion. Second, a self-oscillated noise-shaping integrating dual-slope (DS) converter is used to digitize this magnitude. The proposed converter uses time instead of amplitude resolution to generate a multibit digital output stream. In addition it performs noise shaping of the quantization error to reduce measurement time. This article shows the effectiveness of this method by measurements performed on a prototype, designed and fabricated using standard 0.13 mu m CMOS technology. Experimental measurements show that the CDC achieves a resolution of 17 bits, with an effective area of 0.317 mm(2), which means a pressure resolution of 1 Pa, while consuming 146 mu A from a 1.5 V power supply.This work has been funded by Marie Curie project SIMIC, Grant Agreement No. 610484, funded by grants from the European Union (Research Executive Agency) and TEC2014-56879-R of CICYT, Spain.Publicad

An Implantable Low Pressure Biosensor Transponder

The human body’s intracranial pressure (ICP) is a critical element in sustaining healthy blood flow to the brain while allowing adequate volume for brain tissue within the relatively rigid structure of the cranium. Disruptions in the body’s maintenance of intracranial pressure are often caused by hemorrhage, tumors, edema, or excess cerebral spinal fluid resulting in treatments that are estimated to globally cost up to approximately five billion dollars annually. A critical element in the contemporary management of acute head injury, intracranial hemorrhage, stroke, or other conditions resulting in intracranial hypertension, is the real-time monitoring of ICP. Currently such monitoring can only take place short-term within an acute care hospital, is prone to measurement drift, and is comprised of externally tethered pressure sensors that are temporarily implanted into the brain, thus carrying a significant risk of infection. To date, reliable, low drift, completely internalized, long-term ICP monitoring devices remain elusive. In addition to being safer and more reliable in the short-term, such a device would expand the use of ICP monitoring for the management of chronic diseases involving ICP hypertension and further expand research into these disorders. This research studies the current challenges of existing ICP monitoring systems and investigates opportunities for potentially allowing long-term implantable bio-pressure sensing, facilitating possible improvements in treatment strategies. Based upon the research, this thesis evaluates piezo-resistive strain sensing for low power, sub-millimeter of mercury resolution, in application to implantable intracranial pressure sensing

Integrated temperature sensors in deep sub-micron CMOS technologies

textIntegrated temperature sensors play an important role in enhancing the performance of on-chip power and thermal management systems in today's highly-integrated system-on-chip (SoC) platforms, such as microprocessors. Accurate on-chip temperature measurement is essential to maximize the performance and reliability of these SoCs. However, due to non-uniform power consumption by different functional blocks, microprocessors have fairly large thermal gradient (and variation) across their chips. In the case of multi-core microprocessors for example, there are task-specific thermal gradients across different cores on the same die. As a result, multiple temperature sensors are needed to measure the temperature profile at all relevant coordinates of the chip. Subsequently, the results of the temperature measurements are used to take corrective measures to enhance the performance, or save the SoC from catastrophic over-heating situations which can cause permanent damage. Furthermore, in a large multi-core microprocessor, it is also imperative to continuously monitor potential hot-spots that are prone to thermal runaway. The locations of such hot spots depend on the operations and instruction the processor carries out at a given time. Due to practical limitations, it is an overkill to place a big size temperature sensor nearest to all possible hot spots. Thus, an ideal on-chip temperature sensor should have minimal area so that it can be placed non-invasively across the chip without drastically changing the chip floor plan. In addition, the power consumption of the sensors should be very low to reduce the power budget overhead of thermal monitoring system, and to minimize measurement inaccuracies due to self-heating. The objective of this research is to design an ultra-small size and ultra-low power temperature sensor such that it can be placed in the intimate proximity of all possible hot spots across the chip. The general idea is to use the leakage current of a reverse-bias p-n junction diode as an operand for temperature sensing. The tasks within this project are to examine the theoretical aspect of such sensors in both Silicon-On-Insulator (SOI), and bulk Complementary Metal-Oxide Semiconductor (CMOS) technologies, implement them in deep sub-micron technologies, and ultimately evaluate their performances, and compare them to existing solutions.Electrical and Computer Engineerin

Temperature To Digital Converter Design And Measurement

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2016Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2016Bu çalışmada AMS 0.35u CMOS teknolojisinde 12 bitlik bir sıcaklık sayısal dönüştürücü tasalarlandı ve serimi yapıldı. Tasarlanan dönüştürücü Euro Practice aracılığıyla İTÜ VLSI Labs finans desteği ile üretildi. Dönüştürücünün yonga boyutları 1024um X 600um 0.6144 mm2 iken giriş çıkış padleri ve ESD elamanlar ile birlikte toplamda 1.43 mm2 alan kaplamaktadır. Simulasyon sonuçları ile -40C 85C sıcaklık aralığıda 12 bitlik 0.25C çözünürlük gösterilmiş ve ölçüm sonuçları ile yine aynı sıcaklık aralığında 10 bitlik 1C çözünürlük doğrulanmıştır.Temperature to digital converter is designed and taped-out using AMS035HB4 process. The dimension of the IC core is 1024um X 600um while full chip with esd and pad rings occupying 1024um X 1395um. The simulation results show that 12 bits temperature to digital conversion is achieved with 0.25C resolution while measurement verifies 10 bits temperature to digital conversion with 1 C resolution.Yüksek LisansM.Sc

Power efficient, event driven data acquisition and processing using asynchronous techniques

PhD ThesisData acquisition systems used in remote environmental monitoring equipment and biological sensor nodes rely on limited energy supply soured from either energy harvesters or battery to perform their functions. Among the building blocks of these systems are power hungry Analogue to Digital Converters and Digital Signal Processors which acquire and process samples at predetermined rates regardless of the monitored signal’s behavior. In this work we investigate power efficient event driven data acquisition and processing techniques by implementing an asynchronous ADC and an event driven power gated Finite Impulse Response (FIR) filter. We present an event driven single slope ADC capable of generating asynchronous digital samples based on the input signal’s rate of change. It utilizes a rate of change detection circuit known as the slope detector to determine at what point the input signal is to be sampled. After a sample has been obtained it’s absolute voltage value is time encoded and passed on to a Time to Digital Converter (TDC) as part of a pulse stream. The resulting digital samples generated by the TDC are produced at a rate that exhibits the same rate of change profile as that of the input signal. The ADC is realized in 0.35mm CMOS process, covers a silicon area of 340mm by 218mm and consumes power based on the input signal’s frequency. The samples from the ADC are asynchronous in nature and exhibit random time periods between adjacent samples. In order to process such asynchronous samples we present a FIR filter that is able to successfully operate on the samples and produce the desired result. The filter also poses the ability to turn itself off in-between samples that have longer sample periods in effect saving power in the process

Ultra-low power mixed-signal frontend for wearable EEGs

Electronics circuits are ubiquitous in daily life, aided by advancements in the chip design industry, leading to miniaturised solutions for typical day to day problems. One of the critical healthcare areas helped by this advancement in technology is electroencephalography (EEG). EEG is a non-invasive method of tracking a person's brain waves, and a crucial tool in several healthcare contexts, including epilepsy and sleep disorders. Current ambulatory EEG systems still suffer from limitations that affect their usability. Furthermore, many patients admitted to emergency departments (ED) for a neurological disorder like altered mental status or seizures, would remain undiagnosed hours to days after admission, which leads to an elevated rate of death compared to other conditions. Conducting a thorough EEG monitoring in early-stage could prevent further damage to the brain and avoid high mortality. But lack of portability and ease of access results in a long wait time for the prescribed patients. All real signals are analogue in nature, including brainwaves sensed by EEG systems. For converting the EEG signal into digital for further processing, a truly wearable EEG has to have an analogue mixed-signal front-end (AFE). This research aims to define the specifications for building a custom AFE for the EEG recording and use that to review the suitability of the architectures available in the literature. Another critical task is to provide new architectures that can meet the developed specifications for EEG monitoring and can be used in epilepsy diagnosis, sleep monitoring, drowsiness detection and depression study. The thesis starts with a preview on EEG technology and available methods of brainwaves recording. It further expands to design requirements for the AFE, with a discussion about critical issues that need resolving. Three new continuous-time capacitive feedback chopped amplifier designs are proposed. A novel calibration loop for setting the accurate value for a pseudo-resistor, which is a crucial block in the proposed topology, is also discussed. This pseudoresistor calibration loop achieved the resistor variation of under 8.25%. The thesis also presents a new design of a curvature corrected bandgap, as well as a novel DDA based fourth-order Sallen-Key filter. A modified sensor frontend architecture is then proposed, along with a detailed analysis of its implementation. Measurement results of the AFE are finally presented. The AFE consumed a total power of 3.2A (including ADC, amplifier, filter, and current generation circuitry) with the overall integrated input-referred noise of 0.87V-rms in the frequency band of 0.5-50Hz. Measurement results confirmed that only the proposed AFE achieved all defined specifications for the wearable EEG system with the smallest power consumption than state-of-art architectures that meet few but not all specifications. The AFE also achieved a CMRR of 131.62dB, which is higher than any studied architectures.Open Acces