An Input Power-Aware Maximum Efficiency Tracking Technique for Energy Harvesting in IoT Applications

The Internet of Things (IoT) enables intelligent monitoring and management in many applications such as industrial and biomedical systems as well as environmental and infrastructure monitoring. As a result, IoT requires billions of wireless sensor network (WSN) nodes equipped with a microcontroller and transceiver. As many of these WSN nodes are off-grid and small-sized, their limited-capacity batteries need periodic replacement. To mitigate the high costs and challenges of these battery replacements, energy harvesting from ambient sources is vital to achieve energy-autonomous operation. Energy harvesting for WSNs is challenging because the available energy varies significantly with ambient conditions and in many applications, energy must be harvested from ultra-low power levels. To tackle these stringent power constraints, this dissertation proposes a discontinuous charging technique for switched-capacitor converters that improves the power conversion efficiency (PCE) at low input power levels and extends the input power harvesting range at which high PCE is achievable. Discontinuous charging delivers current to energy storage only during clock non-overlap time. This enables tuning of the output current to minimize converter losses based on the available input power. Based on this fundamental result, an input power-aware, two-dimensional efficiency tracking technique for WSNs is presented. In addition to conventional switching frequency control, clock nonoverlap time control is introduced to adaptively optimize the power conversion efficiency according to the sensed ambient power levels. The proposed technique is designed and simulated in 90nm CMOS with post-layout extraction. Under the same input and output conditions, the proposed system maintains at least 45% PCE at 4μW input power, as opposed to a conventional continuous system which requires at least 18.7μW to maintain the same PCE. In this technique, the input power harvesting range is extended by 1.5x. The technique is applied to a WSN implementation utilizing the IEEE 802.15.4- compatible GreenNet communications protocol for industrial and wearable applications. This allows the node to meet specifications and achieve energy autonomy when deployed in harsher environments where the input power is 49% lower than what is required for conventional operation

Low Power Circuit Design in Sustainable Self Powered Systems for IoT Applications

The Internet-of-Things (IoT) network is being vigorously pushed forward from many fronts in diverse research communities. Many problems are still there to be solved, and challenges are found among its many levels of abstraction. In this thesis we give an overview of recent developments in circuit design for ultra-low power transceivers and energy harvesting management units for the IoT. The first part of the dissertation conducts a study of energy harvesting interfaces and optimizing power extraction, followed by power management for energy storage and supply regulation. we give an overview of the recent developments in circuit design for ultra-low power management units, focusing mainly in the architectures and techniques required for energy harvesting from multiple heterogeneous sources. Three projects are presented in this area to reach a solution that provides reliable continuous operation for IoT sensor nodes in the presence of one or more natural energy sources to harvest from. The second part focuses on wireless transmission, To reduce the power consumption and boost the Tx energy efficiency, a novel delay cell exploiting current reuse is used in a ring-oscillator employed as the local oscillator generator scheme. In combination with an edge-combiner power amplifier, the Tx showed a measured energy efficiency of 0.2 nJ=bit and a normalized energy efficiency of 3.1 nJ=bit:mW when operating at output power levels up to -10 dBm and data rates of 3 Mbps

Low-Power Energy Efficient Circuit Techniques for Small IoT Systems

Although the improvement in circuit speed has been limited in recent years, there has been increased focus on the internet of things (IoT) as technology scaling has decreased circuit size, power usage and cost. This trend has led to the development of many small sensor systems with affordable costs and diverse functions, offering people convenient connection with and control over their surroundings. This dissertation discusses the major challenges and their solutions in realizing small IoT systems, focusing on non-digital blocks, such as power converters and analog sensing blocks, which have difficulty in following the traditional scaling trends of digital circuits. To accommodate the limited energy storage and harvesting capacity of small IoT systems, this dissertation presents an energy harvester and voltage regulators with low quiescent power and good efficiency in ultra-low power ranges. Switched-capacitor-based converters with wide-range energy-efficient voltage-controlled oscillators assisted by power-efficient self-oscillating voltage doublers and new cascaded converter topologies for more conversion ratio configurability achieve efficient power conversion down to several nanowatts. To further improve the power efficiency of these systems, analog circuits essential to most wireless IoT systems are also discussed and improved. A capacitance-to-digital sensor interface and a clocked comparator design are improved by their digital-like implementation and operation in phase and frequency domain. Thanks to the removal of large passive elements and complex analog blocks, both designs achieve excellent area reduction while maintaining state-of-art energy efficiencies. Finally, a technique for removing dynamic voltage and temperature variations is presented as smaller circuits in advanced technologies are more vulnerable to these variations. A 2-D simultaneous feedback control using an on-chip oven control locks the supply voltage and temperature of a small on-chip domain and protects circuits in this locked domain from external voltage and temperature changes, demonstrating 0.0066 V/V and 0.013 °C/°C sensitivities to external changes. Simple digital implementation of the sensors and most parts of the control loops allows robust operation within wide voltage and temperature ranges.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138743/1/wanyeong_1.pd

Autonomous electrical current monitoring system for aircraft

Aircraft monitoring systems offer enhanced safety, reliability, reduced maintenance cost and improved overall flight efficiency. Advancements in wireless sensor networks (WSN) are enabling unprecedented data acquisition functionalities, but their applicability is restricted by power limitations, as batteries require replacement or recharging and wired power adds weight and detracts from the benefits of wireless technology. In this paper, an energy autonomous WSN is presented for monitoring the structural current in aircraft structures. A hybrid inductive/hall sensing concept is introduced demonstrating 0.5 A resolution, < 2% accuracy and frequency independence, for a 5 A – 100 A RMS, DC-800 Hz current and frequency range, with 35 mW active power consumption. An inductive energy harvesting power supply with magnetic flux funnelling, reactance compensation and supercapacitor storage is demonstrated to provide 0.16 mW of continuous power from the 65 μT RMS field of a 20 A RMS, 360 Hz structural current. A low-power sensor node platform with a custom multi-mode duty cycling network protocol is developed, offering cold starting network association and data acquisition/transmission functionality at 50 μW and 70 μW average power respectively. WSN level operation for 1 minute for every 8 minutes of energy harvesting is demonstrated. The proposed system offers a unique energy autonomous WSN platform for aircraft monitoring

Sub 1V Charge Pump based Micro Scale Energy Harvesting for Low Power Application

Harvesting energy from our environment is a promising solution to provide power to wireless sensor network, wearable devices and biomedical implantation. Now a days, usage of battery power system has disappeared because of replacement issues, installation costs every periodic year and the possibility of health hazard in the case of biomedical implants. Considering these issues, energy harvesting proves to be the most feasible and convenient option in the case of wearable devices and biomedical implantation. Hence, we have focused on indoor single solar cell energy harvesting to power ultra-low power load. The tree topology DC-DC converter is used for power management circuit with optimized efficiency. High efficiency is achieved by using ZVT MOSCAP. The power management circuit includes DC-DC converter and feed forward maximum power point tracking algorithm to transfer maximum power from the single solar cell. The system has ultra-low power battery protection and input condition sensor circuit to extend the life of the battery by protecting from overcharging and over discharging. Also, cold start up circuit is used to run the system when battery voltage drains out to zero. The objective of this system to make complete energy harvester unit is to drive wide range of ultra-low power applications. We have driven the ZigBee receiver to validate our system and the system works effectively

Power Management Circuits for Energy Harvesting Applications

Energy harvesting is the process of converting ambient available energy into usable electrical energy. Multiple types of sources are can be used to harness environmental energy: solar cells, kinetic transducers, thermal energy, and electromagnetic waves. This dissertation proposal focuses on the design of high efficiency, ultra-low power, power management units for DC energy harvesting sources. New architectures and design techniques are introduced to achieve high efficiency and performance while achieving maximum power extraction from the sources. The first part of the dissertation focuses on the application of inductive switching regulators and their use in energy harvesting applications. The second implements capacitive switching regulators to minimize the use of external components and present a minimal footprint solution for energy harvesting power management. Analysis and theoretical background for all switching regulators and linear regulators are described in detail. Both solutions demonstrate how low power, high efficiency design allows for a self-sustaining, operational device which can tackle the two main concerns for energy harvesting: maximum power extraction and voltage regulation. Furthermore, a practical demonstration with an Internet of Things type node is tested and positive results shown by a fully powered device from harvested energy. All systems were designed, implemented and tested to demonstrate proof-of-concept prototypes

Ultra-Low Power Transmitter and Power Management for Internet-of-Things Devices

Two of the most critical components in an Internet-of-Things (IoT) sensing and transmitting node are the power management unit (PMU) and the wireless transmitter (Tx). The desire for longer intervals between battery replacements or a completely self-contained, battery-less operation via energy harvesting transducers and circuits in IoT nodes demands highly efficient integrated circuits. This dissertation addresses the challenge of designing and implementing power management and Tx circuits with ultra-low power consumption to enable such efficient operation. The first part of the dissertation focuses on the study and design of power management circuits for IoT nodes. This opening portion elaborates on two different areas of the power management field: Firstly, a low-complexity, SPICE-based model for general low dropout (LDO) regulators is demonstrated. The model aims to reduce the stress and computation times in the final stages of simulation and verification of Systems-on-Chip (SoC), including IoT nodes, that employ large numbers of LDOs. Secondly, the implementation of an efficient PMU for an energy harvesting system based on a thermoelectric generator transducer is discussed. The PMU includes a first-in-its-class LDO with programmable supply noise rejection for localized improvement in the suppression. The second part of the dissertation addresses the challenge of designing an ultra- low power wireless FSK Tx in the 900 MHz ISM band. To reduce the power consumption and boost the Tx energy efficiency, a novel delay cell exploiting current reuse is used in a ring-oscillator employed as the local oscillator generator scheme. In combination with an edge-combiner PA, the Tx showed a measured energy efficiency of 0.2 nJ/bit and a normalized energy efficiency of 3.1 nJ/(bit∙mW) when operating at output power levels up to -10 dBm and data rates of 3 Mbps. To close this dissertation, the implementation of a supply-noise tolerant BiCMOS ring-oscillator is discussed. The combination of a passive, high-pass feedforward path from the supply to critical nodes in the selected delay cell and a low cost LDO allow the oscillator to exhibit power supply noise rejection levels better than –33 dB in experimental results

A Study on Energy-Efficient Inductor Current Controls for Maximum Energy Delivery in Battery-free Buck Converter

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2017. 2. 김재하.A discontinuous conduction mode (DCM) buck converter, which acts as a voltage regulator in battery-free applications, is proposed to maximize the ener-gy delivery to the load system. In this work, we focus the energy loss problem during start-up and steady-state operation of the buck converter, which severely limits the energy delivery. Especially, the energy loss problem arises from the fact that there is no constant power source such as a battery and the only a small amount of energy harvested from the ambient energy sources is available. To address such energy loss problem, this dissertation proposes optimal induc-tor current control techniques at each operation to greatly reduce the energy losses. First, a switching-based stepwise capacitor charging scheme is presented that can charge the output capacitor with constant inductor current during start-up operation. By switching the inductor with gradually incrementing duty-cycle ratios in a stepwise fashion, the buck converter can make the inductor current a constant current source, which can greatly reduce the start-up energy loss com-pared to that in the conventional capacitor charging scheme with a voltage source. Second, a variable on-time (VOT) pulse-frequency-modulation (PFM) scheme is presented that can keep the peak inductor current constant during steady-state operation. By adaptively varying the on-time according to the op-erating voltage conditions of the buck converter, it can suppress the voltage ripple and improve the power efficiency even with a small output capacitor. Third, an adaptive off-time positioning zero-crossing detector (AOP-ZCD) is presented that can adaptively position the turn-off timing of the low-side switch close to the zero-inductor-current timing by predicting the inductor current waveform without using a power-hungry continuous-time ZCD. To demonstrate the proposed design concepts, the prototype battery-free wireless remote switch including the piezoelectric energy harvester and the proposed buck converter was fabricated in a 250 nm high-voltage CMOS technology. It can harvest a total energy of 246 μJ from a single button press action of a 300-mm2 lead magnesium niobate-lead titanate (PMN-PT) piezoelectric disc, and deliver more than 200 μJ to the load, which is sufficient to transmit a 4-byte-long message via 2.4-GHz wireless USB channel over a 10-m distance. If such battery-free application does not use the proposed buck converter, the energy losses in-curred at the buck converter would be larger than the energy harvested, and therefore it cannot operate with a single button-pressing action. Furthermore, thanks to the proposed energy efficient buck converter, the battery-free wire-less remote switch can be realized by using a cheaper PZT piezoelectric source, which can achieve a 10× cost reduction.CHAPTER 1 INTRODUCTION 1 1.1 MOTIVATION 1 1.2 THESIS CONTRIBUTION AND ORGANIZATION 6 CHAPTER 2 OPERATION MODE AND OVERALL ARCHITECTURE 8 2.1 TOPOLOGY SELECTION 8 2.2 PRINCIPLE OF OPERATION 11 2.2.1 BASIC OPERATION IN CCM 12 2.2.2 BASIC OPERATION IN DCM 15 2.3 OPERATION MODE 17 2.4 OVERALL ARCHITECTURE 19 CHAPTER 3 OPTIMAL INDUCTOR CURRENT CONTROLS FOR MAXIMUM ENERGY DELIVERY 23 3.1 CONSTANT INDUCTOR CURRENT CONTROL WITH SWITCHING-BASED STEPWISE CAPACITOR CHARGING SCHEME 24 3.1.1 CONVENTIONAL CHARGING SCHEME WITH A SWITCH 24 3.1.2 ADIABATIC STEPWISE CHARGING 27 3.1.3 PROPOSED START-UP SCHEME 29 3.2 CONSTANT INDUCTOR PEAK CURRENT CONTROL WITH VARIABLE ON-TIME PFM SCHEME 35 3.2.1 BASIC OPERATION OF PFM BUCK CONVERTER 35 3.2.2 CONSTANT ON-TIME PFM SCHEME 39 3.2.3 VARIABLE ON-TIME PFM SCHEME 41 3.3 INDUCTOR CURRENT PREDICTION WITH ADAP-TIVE OFF-TIME POSITIONING ZCD (AOP-ZCD) 44 3.3.1 PREVIOUS SAMPLING-BASED ZCD 44 3.3.2 PROPOSED ADAPTIVE OFF-TIME POSITIONING ZCD 47 CHAPTER 4 CIRCUIT IMPLEMENTATION 49 4.1 CIRCUIT IMPLEMENTATION OF SWITCHING-BASED STEPWISE CAPACITOR CHARGER 49 4.1.1 VOLTAGE DETECTOR (VD) 50 4.1.2 DIGITAL PULSE WIDTH MODULATOR (DPWM) 52 4.1.3 PROGRAMMABLE DUTY-CYCLE CONTROLLER (DCC) 55 4.1.4 SWITCHED CAPACITOR (SC) STEP-DOWN CONVERTER 57 4.2 CIRCUIT IMPLEMENTATION OF VARIABLE ON-TIME PULSE GENERATOR 59 4.3 CIRCUIT IMPLEMENTATION OF ADAPTIVE OFF-TIME POSITIONING ZCD 64 4.3.1 ADAPTIVE OFF-TIME (AOT) PULSE GENERATOR 64 4.3.2 TIMING ERROR DETECTOR AND SHIFT-REGISTER 68 CHAPTER 5 MEASUREMENT RESULTS OF PROPOSED BUCK CONVERTER 70 5.1 SWITCHING-BASED STEPWISE CAPACITOR CHARGER 71 5.2 STEADY-STATE PERFORMANCE WITH VOT PULSE GENERATOR AND AOP-ZCD 74 CHAPTER 6 REALIZATION OF BATTERY-FREE WIRELESS REMOTE SWITCH 84 6.1 KEY BUILDING BLOCKS OF BATTERY-FREE WIRELESS REMOTE SWITCH 85 6.2 PIEZOELECTRIC ENERGY HARVESTER WITH P-SSHI RECTIFIER 86 6.2.1 ANALYSIS ON SINGLE-PULSED ENERGY HARVESTING 88 6.2.2 PROPOSED PIEZOELECTRIC ENERGY HARVESTER 91 6.2.3 CIRCUIT IMPLEMENTATION 93 6.3 MEASUREMENT RESULTS OF BATTERY-FREE WIRELESS SWITCH 96 CHAPTER 7 CONCLUSION 101 BIBLIOGRAPHY 103 초 록 110Docto

FULLY AUTONOMOUS SELF-POWERED INTELLIGENT WIRELESS SENSOR FOR REAL-TIME TRAFFIC SURVEILLANCE IN SMART CITIES

Reliable, real-time traffic surveillance is an integral and crucial function of the 21st century intelligent transportation systems (ITS) network. This technology facilitates instantaneous decision-making, improves roadway efficiency, and maximizes existing transportation infrastructure capacity, making transportation systems safe, efficient, and more reliable. Given the rapidly approaching era of smart cities, the work detailed in this dissertation is timely in that it reports on the design, development, and implementation of a novel, fully-autonomous, self-powered intelligent wireless sensor for real-time traffic surveillance. Multi-disciplinary, innovative integration of state-of-the-art, ultra-low-power embedded systems, smart physical sensors, and the wireless sensor network—powered by intelligent algorithms—are the basis of the developed Intelligent Vehicle Counting and Classification Sensor (iVCCS) platform. The sensor combines an energy-harvesting subsystem to extract energy from multiple sources and enable sensor node self-powering aimed at potentially indefinite life. A wireless power receiver was also integrated to remotely charge the sensor’s primary battery. Reliable and computationally efficient intelligent algorithms for vehicle detection, speed and length estimation, vehicle classification, vehicle re-identification, travel-time estimation, time-synchronization, and drift compensation were fully developed, integrated, and evaluated. Several length-based vehicle classification schemes particular to the state of Oklahoma were developed, implemented, and evaluated using machine learning algorithms and probabilistic modeling of vehicle magnetic length. A feature extraction employing different techniques was developed to determine suitable and efficient features for magnetic signature-based vehicle re-identification. Additionally, two vehicle re-identification models based on matching vehicle magnetic signature from a single magnetometer were developed. Comprehensive system evaluation and extensive data analyses were performed to fine-tune and validate the sensor, ensuring reliable and robust operation. Several field studies were conducted under various scenarios and traffic conditions on a number of highways and urban roads and resulted in 99.98% detection accuracy, 97.4782% speed estimation accuracy, and 97.6951% classification rate when binning vehicles into four groups based on their magnetic length. Threshold-based, re-identification results revealed 65.25%~100% identification rate for a window of 25~500 vehicles. Voting-based, re-identification evaluation resulted in 90~100% identification rate for a window of 25~500 vehicles. The developed platform is portable and cost-effective. A single sensor node costs only $30 and can be installed for short-term use (e.g., work zone safety, traffic flow studies, roadway and bridge design, traffic management in atypical situations), as well as long-term use (e.g., collision avoidance at intersections, traffic monitoring) on highways, roadways, or roadside surfaces. The power consumption assessment showed that the sensor is operational for several years. The iVCCS platform is expected to significantly supplement other data collection methods used for traffic monitoring throughout the United States. The technology is poised to play a vital role in tomorrow’s smart cities