Contribution to time domain readout circuits design for multi-standard sensing system for low voltage supply and high-resolution applications

Mención Internacional en el título de doctorThis research activity has the purpose of open new possibilities in the design of capacitance-to-digital converters (CDCs) by developing a solution based on time domain conversion. This can be applied to applications related with the Internet-of-Things (IoT). These applications are present in any electronic devices where sensing is needed. To be able to reduce the area of the whole system with the required performance, micro-electromechanical systems (MEMS) sensors are used in these applications. We propose a new family of sensor readout electronics to be integrated with MEMS sensors. Within the time domain converters, Dual Slope (DS) topology is very interesting to explore a new compromise between performances, area and power consumption. DS topology has been extensively used in instrumentation. The simplicity and robustness of the blocks inside classical DS converters it is the main advantage. However, they are not efficient for applications where higher bandwidth is required. To extend the bandwidth, DS converters have been introduced into ΔΣ loops. This topology has been named as integrating converters. They increase the bandwidth compare to classical DS architecture but at the expense of higher complexity. In this work we propose the use of a new family of DS converters that keep the advantages of the classical architecture and introduce noise shaping. This way the bandwidth is increased without extra blocks. The Self-Compensated noise-shaped DS converter (the name given to the new topology) keeps the signal transfer function (STF) and the noise transfer function (NTF) of Integrating converters. However, we introduce a new arrangement in the core of the converter to do noise shaping without extra circuitry. This way the simplicity of the architecture is preserved. We propose to use the Self-Compensated DS converter as a CDC for MEMS sensors. This work makes a study of the best possible integration of the two blocks to keep the signal integrity considering the electromechanical behavior of the sensor. The purpose of this front-end is to be connected to any kind of capacitive MEMS sensor. However, to prove the concepts developed in this thesis the architecture has been connected to a pressure MEMS sensor. An experimental prototype was implemented in 130-nm CMOS process using the architecture mentioned before. A peak SNR of 103.9 dB (equivalent to 1Pa) has been achieved within a time measurement of 20 ms. The final prototype has a power consumption of 220 μW with an effective area of 0.317 mm2. The designed architecture shows good performance having competitive numbers against high resolution topologies in amplitude domain.Esta actividad de investigación tiene el propósito de explorar nuevas posibilidades en el diseño de convertidores de capacitancia a digital (CDC) mediante el desarrollo de una solución basada en la conversión en el dominio del tiempo. Estos convertidores se pueden utilizar en aplicaciones relacionadas con el mercado del Internet-de-las-cosas (IoT). Hoy en día, estas aplicaciones están presentes en cualquier dispositivo electrónico donde se necesite sensar una magnitud. Para poder reducir el área de todo el sistema con el rendimiento requerido, se utilizan sensores de sistemas micro-electromecánicos (MEMS) en estas aplicaciones. Proponemos una nueva familia de electrónica de acondicionamiento para integrar con sensores MEMS. Dentro de los convertidores de dominio de tiempo, la topología del doble-rampa (DS) es muy interesante para explorar un nuevo compromiso entre rendimiento, área y consumo de energía. La topología de DS se ha usado ampliamente en instrumentación. La simplicidad y la solidez de los bloques dentro de los convertidores DS clásicos es la principal ventaja. Sin embargo, no son eficientes para aplicaciones donde se requiere mayor ancho de banda. Para ampliar el ancho de banda, los convertidores DS se han introducido en bucles ΔΣ. Esta topología ha sido nombrada como Integrating converters. Esta topología aumenta el ancho de banda en comparación con la arquitectura clásica de DS, pero a expensas de una mayor complejidad. En este trabajo, proponemos el uso de una nueva familia de convertidores DS que mantienen las ventajas de la arquitectura clásica e introducen la configuración del ruido. De esta forma, el ancho de banda aumenta sin bloques adicionales. El convertidor Self-Compensated noise-shaped DS (el nombre dado a la nueva topología) mantiene la función de transferencia de señal (STF) y la función de transferencia de ruido (NTF) de los Integrating converters. Sin embargo, presentamos una nueva topología en el núcleo del convertidor para conformar el ruido sin circuitos adicionales. De esta manera, se preserva la simplicidad de la arquitectura. Proponemos utilizar el Self-Compensated noise-shaped DS como un CDC para sensores MEMS. Este trabajo hace un estudio de la mejor integración posible de los dos bloques para mantener la integridad de la señal considerando el comportamiento electromecánico del sensor. El propósito de este circuito de acondicionamiento es conectarse a cualquier tipo de sensor MEMS capacitivo. Sin embargo, para demostrar los conceptos desarrollados en esta tesis, la arquitectura se ha conectado a un sensor MEMS de presión. Se ha implementado dos prototipos experimentales en un proceso CMOS de 130-nm utilizando la arquitectura mencionada anteriormente. Se ha logrado una relación señal-ruido máxima de 103.9 dB (equivalente a 1 Pa) con un tiempo de medida de 20 ms. El prototipo final tiene un consumo de energía de 220 μW con un área efectiva de 0.317 mm2. La arquitectura diseñada muestra un buen rendimiento comparable con las arquitecturas en el dominio de la amplitud que muestran resoluciones equivalentes.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Pieter Rombouts.- Secretario: Alberto Rodríguez Pérez.- Vocal: Dietmar Strãußnig

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

Sub-Femto-Farad Resolution Electronic Interfaces for Integrated Capacitive Sensors: A Review

Capacitance detection is a universal transduction mechanism used in a wide variety of sensors and applications. It requires an electronic front-end converting the capacitance variation into another more convenient physical variable, ultimately determining the performance of the whole sensor. In this paper we present a comprehensive review of the different signal conditioning front-end topologies targeted in particular at sub-femtofarad resolution. Main design equations and analysis of the limits due to noise are reported in order to provide the designer with guidelines for choosing the most suitable topology according to the main design specifications, namely energy consumption, area occupation, measuring time and resolution. A data-driven comparison of the different solutions in literature is also carried out revealing that resolution, measuring time, area occupation and energy/conversion lower than 100 aF, 1 ms 0.1 mm2, and 100 pJ/conv. can be obtained by capacitance to digital topologies, which therefore allow to get the best compromise among all design specifications

?????? ?????? ???????????? ?????? ???????????? ??????????????? ?????????????????? ??? ???????????????

Department of Electrical EngineeringA Sensor system is advanced along sensor technologies are developed. The performance improvement of sensor system can be expected by using the internet of things (IoT) communication technology and artificial neural network (ANN) for data processing and computation. Sensors or systems exchanged the data through this wireless connectivity, and various systems and applications are possible to implement by utilizing the advanced technologies. And the collected data is computed using by the ANN and the efficiency of system can be also improved. Gas monitoring system is widely need from the daily life to hazardous workplace. Harmful gas can cause a respiratory disease and some gas include cancer-causing component. Even though it may cause dangerous situation due to explosion. There are various kinds of hazardous gas and its characteristics that effect on human body are different each gas. The optimal design of gas monitoring system is necessary due to each gas has different criteria such as the permissible concentration and exposure time. Therefore, in this thesis, conventional sensor system configuration, operation, and limitation are described and gas monitoring system with wireless connectivity and neural network is proposed to improve the overall efficiency. As I already mentioned above, dangerous concentration and permissible exposure time are different depending on gas types. During the gas monitoring, gas concentration is lower than a permissible level in most of case. Thus, the gas monitoring is enough with low resolution for saving the power consumption in this situation. When detecting the gas, the high-resolution is required for the accurate concentration detecting. If the gas type is varied in the above situation, the amount of calculation increases exponentially. Therefore, in the conventional systems, target specifications are decided by the highest requirement in the whole situation, and it occurs increasing the cost and complexity of readout integrated circuit (ROIC) and system. In order to optimize the specification, the ANN and adaptive ROIC are utilized to compute the complex situation and huge data processing. Thus, gas monitoring system with learning-based algorithm is proposed to improve its efficiency. In order to optimize the operation depending on situation, dual-mode ROIC that monitoring mode and precision mode is implemented. If the present gas concentration is decided to safe, monitoring mode is operated with minimal detecting accuracy for saving the power consumption. The precision mode is switched when the high-resolution or hazardous situation are detected. The additional calibration circuits are necessary for the high-resolution implementation, and it has more power consumption and design complexity. A high-resolution Analog-to-digital converter (ADC) is kind of challenges to design with efficiency way. Therefore, in order to reduce the effective resolution of ADC and power consumption, zooming correlated double sampling (CDS) circuit and prediction successive approximation register (SAR) ADC are proposed for performance optimization into precision mode. A Microelectromechanical systems (MEMS) based gas sensor has high-integration and high sensitivity, but the calibration is needed to improve its low selectivity. Conventionally, principle component analysis (PCA) is used to classify the gas types, but this method has lower accuracy in some case and hard to verify in real-time. Alternatively, ANN is powerful algorithm to accurate sensing through collecting the data and training procedure and it can be verified the gas type and concentration in real-time. ROIC was fabricated in complementary metal-oxide-semiconductor (CMOS) 180-nm process and then the efficiency of the system with adaptive ROIC and ANN algorithm was experimentally verified into gas monitoring system prototype. Also, Bluetooth supports wireless connectivity to PC and mobile and pattern recognition and prediction code for SAR ADC is performed in MATLAB. Real-time gas information is monitored by Android-based application in smartphone. The dual-mode operation, optimization of performance and prediction code are adjusted with microcontroller unit (MCU). Monitoring mode is improved by x2.6 of figure-of-merits (FoM) that compared with previous resistive interface.clos

Advances in Solid State Circuit Technologies

This book brings together contributions from experts in the fields to describe the current status of important topics in solid-state circuit technologies. It consists of 20 chapters which are grouped under the following categories: general information, circuits and devices, materials, and characterization techniques. These chapters have been written by renowned experts in the respective fields making this book valuable to the integrated circuits and materials science communities. It is intended for a diverse readership including electrical engineers and material scientists in the industry and academic institutions. Readers will be able to familiarize themselves with the latest technologies in the various fields

Integrated Circuits and Systems for Smart Sensory Applications

Connected intelligent sensing reshapes our society by empowering people with increasing new ways of mutual interactions. As integration technologies keep their scaling roadmap, the horizon of sensory applications is rapidly widening, thanks to myriad light-weight low-power or, in same cases even self-powered, smart devices with high-connectivity capabilities. CMOS integrated circuits technology is the best candidate to supply the required smartness and to pioneer these emerging sensory systems. As a result, new challenges are arising around the design of these integrated circuits and systems for sensory applications in terms of low-power edge computing, power management strategies, low-range wireless communications, integration with sensing devices. In this Special Issue recent advances in application-specific integrated circuits (ASIC) and systems for smart sensory applications in the following five emerging topics: (I) dedicated short-range communications transceivers; (II) digital smart sensors, (III) implantable neural interfaces, (IV) Power Management Strategies in wireless sensor nodes and (V) neuromorphic hardware

Robust Control of Wide Bandgap Power Electronics Device Enabled Smart Grid

abstract: In recent years, wide bandgap (WBG) devices enable power converters with higher power density and higher efficiency. On the other hand, smart grid technologies are getting mature due to new battery technology and computer technology. In the near future, the two technologies will form the next generation of smart grid enabled by WBG devices. This dissertation deals with two applications: silicon carbide (SiC) device used for medium voltage level interface (7.2 kV to 240 V) and gallium nitride (GaN) device used for low voltage level interface (240 V/120 V). A 20 kW solid state transformer (SST) is designed with 6 kHz switching frequency SiC rectifier. Then three robust control design methods are proposed for each of its smart grid operation modes. In grid connected mode, a new LCL filter design method is proposed considering grid voltage THD, grid current THD and current regulation loop robust stability with respect to the grid impedance change. In grid islanded mode, µ synthesis method combined with variable structure control is used to design a robust controller for grid voltage regulation. For grid emergency mode, multivariable controller designed using H infinity synthesis method is proposed for accurate power sharing. Controller-hardware-in-the-loop (CHIL) testbed considering 7-SST system is setup with Real Time Digital Simulator (RTDS). The real TMS320F28335 DSP and Spartan 6 FPGA control board is used to interface a switching model SST in RTDS. And the proposed control methods are tested. For low voltage level application, a 3.3 kW smart grid hardware is built with 3 GaN inverters. The inverters are designed with the GaN device characterized using the proposed multi-function double pulse tester. The inverter is controlled by onboard TMS320F28379D dual core DSP with 200 kHz sampling frequency. Each inverter is tested to process 2.2 kW power with overall efficiency of 96.5 % at room temperature. The smart grid monitor system and fault interrupt devices (FID) based on Arduino Mega2560 are built and tested. The smart grid cooperates with GaN inverters through CAN bus communication. At last, the three GaN inverters smart grid achieved the function of grid connected to islanded mode smooth transitionDissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Powertrain Architectures and Technologies for New Emission and Fuel Consumption Standards

New powertrain design is highly influenced by CO2 and pollutant limits defined by legislations, the demand of fuel economy in for real conditions, high performances and acceptable cost. To reach the requirements coming from both end-users and legislations, several powertrain architectures and engine technologies are possible (e.g. SI or CI engines), with many new technologies, new fuels, and different degree of electrification. The benefits and costs given by the possible architectures and technology mix must be accurately evaluated by means of objective procedures and tools in order to choose among the best alternatives. This work presents a basic design methodology and a comparison at concept level of the main powertrain architectures and technologies that are currently being developed, considering technical benefits and their cost effectiveness. The analysis is carried out on the basis of studies from the technical literature, integrating missing data with evaluations performed by means of powertrain-vehicle simplified models, considering the most important powertrain architectures. Technology pathways for passenger cars up to 2025 and beyond have been defined. After that, with support of more detailed models and experimentations, the investigation has been focused on the more promising technologies to improve internal combustion engine, such as: water injection, low temperature combustions and heat recovery systems

Design of an Autonomous Platform for Search and Rescue UAV Networks

This project designed and implemented a platform for use in a system of unmanned aerial vehicles (UAVs) capable of human assisted-autonomous and fully autonomous flight for search and rescue applications to improve the speed, efficiency, and safety of search and rescue to benefit both the victims and the rescuers alike. To accomplish this, the platform was designed to be lightweight with long endurance, equipped with specialized search and rescue sensors, and utilizes the paparazzi autopilot system, which is an open source, Linux based autopilot package for flight stability and autonomous control