Very-Large-Scale-Integration Circuit Techniques in Internet-of-Things Applications

Heading towards the era of Internet-of-things (IoT) means both opportunity and challenge for the circuit-design community. In a system where billions of devices are equipped with the ability to sense, compute, communicate with each other and perform tasks in a coordinated manner, security and power management are among the most critical challenges. Physically unclonable function (PUF) emerges as an important security primitive in hardware-security applications; it provides an object-specific physical identifier hidden within the intrinsic device variations, which is hard to expose and reproduce by adversaries. Yet, designing a compact PUF robust to noise, temperature and voltage remains a challenge. This thesis presents a novel PUF design approach based on a pair of ultra-compact analog circuits whose output is proportional to absolute temperature. The proposed approach is demonstrated through two works: (1) an ultra-compact and robust PUF based on voltage-compensated proportional-to-absolute-temperature voltage generators that occupies 8.3× less area than the previous work with the similar robustness and twice the robustness of the previously most compact PUF design and (2) a technique to transform a 6T-SRAM array into a robust analog PUF with minimal overhead. In this work, similar circuit topology is used to transform a preexisting on-chip SRAM into a PUF, which further reduces the area in (1) with no robustness penalty. In this thesis, we also explore techniques for power management circuit design. Energy harvesting is an essential functionality in an IoT sensor node, where battery replacement is cost-prohibitive or impractical. Yet, existing energy-harvesting power management units (EH PMU) suffer from efficiency loss in the two-step voltage conversion: harvester-to-battery and battery-to-load. We propose an EH PMU architecture with hybrid energy storage, where a capacitor is introduced in addition to the battery to serve as an intermediate energy buffer to minimize the battery involvement in the system energy flow. Test-case measurements show as much as a 2.2× improvement in the end-to-end energy efficiency. In contrast, with the drastically reduced power consumption of IoT nodes that operates in the sub-threshold regime, adaptive dynamic voltage scaling (DVS) for supply-voltage margin removal, fully on-chip integration and high power conversion efficiency (PCE) are required in PMU designs. We present a PMU–load co-design based on a fully integrated switched-capacitor DC-DC converter (SC-DC) and hybrid error/replica-based regulation for a fully digital PMU control. The PMU is integrated with a neural spike processor (NSP) that achieves a record-low power consumption of 0.61 µW for 96 channels. A tunable replica circuit is added to assist the error regulation and prevent loss of regulation. With automatic energy-robustness co-optimization, the PMU can set the SC-DC’s optimal conversion ratio and switching frequency. The PMU achieves a PCE of 77.7% (72.2%) at VIN = 0.6 V (1 V) and at the NSP’s margin-free operating point

In-Body Energy Harvesting Power Management Interface for Post Heart Transplantation Monitoring

Deep tissue energy harvesters are of increasing interest in the development of battery-less implantable devices. This paper presents a fully integrated ultra-low quiescent power management interface. It has power optimization and impedance matching between a piezoelectric energy harvester and the functional load that could be potentially powered by the heart's mechanical motions. The circuit has been designed in 0.18-µm CMOS technology. It dissipates 189.8 nW providing two voltage outputs of 1.4 V and 4.2 V. The simulation results show an output power 8.2x times of an ideal full-bridge rectifier without an external power supply. The design has the potential for use in self-powered heart implantable devices as it is capable providing stable output voltages from a cold startup

Circuits and Systems for Energy Harvesting and Internet of Things Applications

The Internet of Things (IoT) continues its growing trend, while new “smart” objects are con-stantly being developed and commercialized in the market. Under this paradigm, every common object will be soon connected to the Internet: mobile and wearable devices, electric appliances, home electronics and even cars will have Internet connectivity. Not only that, but a variety of wireless sensors are being proposed for different consumer and industrial applications. With the possibility of having hundreds of billions of IoT objects deployed all around us in the coming years, the social implications and the economic impact of IoT technology needs to be seriously considered. There are still many challenges, however, awaiting a solution in order to realize this future vision of a connected world. A very important bottleneck is the limited lifetime of battery powered wireless devices. Fully depleted batteries need to be replaced, which in perspective would generate costly maintenance requirements and environmental pollution. However, a very plausible solution to this dilemma can be found in harvesting energy from the ambient. This dissertation focuses in the design of circuits and system for energy harvesting and Internet of Things applications. The first part of this dissertation introduces the research motivation and fundamentals of energy harvesting and power management units (PMUs). The architecture of IoT sensor nodes and PMUs is examined to observe the limitations of modern energy harvesting systems. Moreover, several architectures for multisource harvesting are reviewed, providing a background for the research presented here. Then, a new fully integrated system architecture for multisource energy harvesting is presented. The design methodology, implementation, trade-offs and measurement results of the proposed system are described. The second part of this dissertation focus on the design and implementation of low-power wireless sensor nodes for precision agriculture. First, a sensor node incorporating solar energy harvesting and a dynamic power management strategy is presented. The operation of a wireless sensor network for soil parameter estimation, consisting of four nodes is demonstrated. After that, a solar thermoelectric generator (STEG) prototype for powering a wireless sensor node is proposed. The implemented solar thermoelectric generator demonstrates to be an alternative way to harvest ambient energy, opening the possibility for its use in agricultural and environmental applications. The open problems in energy harvesting for IoT devices are discussed at the end, to delineate the possible future work to improve the performance of EH systems. For all the presented works, proof-of-concept prototypes were fabricated and tested. The measured results are used to verify their correct operation and performance

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

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

Power Management Techniques for Supercapacitor Based IoT Applications

University of Minnesota Ph.D. dissertation. January 2018. Major: Electrical Engineering. Advisor: Ramesh Harjani. 1 computer file (PDF); xi, 89 pages.The emerging internet of things (IoT) technology will connect many untethered devices, e.g. sensors, RFIDs and wearable devices, to improve health lifestyle, automotive, smart buildings, etc. This thesis proposes one typical application of IoT: RFID for blood temperature monitoring. Once the blood is donated and sealed in a blood bag, it is required to be stored in a certain temperature range (+2~+6°C for red cell component) before distribution. The proposed RFID tag is intended to be attached to the blood bag and continuously monitor the environmental temperature during transportation and storage. When a reader approaches, the temperature data is read out and the tag is fully recharged wirelessly within 2 minutes. Once the blood is distributed, the tag can be reset and reused again. Such a biomedical application has a strong aversion to toxic chemicals, so a batteryless design is required for the RFID tag. A passive RFID tag, however, cannot meet the longevity requirement for the monitoring system (at least 1 week). The solution of this thesis is using a supercapacitor (supercap) instead of a battery as the power supply, which not only lacks toxic heavy metals, but also has quicker charge time (~1000x over batteries), larger operating temperature range (-40~+65°C), and nearly infinite shelf life. Although nearly perfect for this RFID application, a supercap has its own disadvantages: lower energy density (~30x smaller than batteries) and unstable output voltage. To solve the quick charging and long lasting requirements of the RFID system, and to overcome the intrinsic disadvantages of supercaps, an overall power management solution is proposed in this thesis. A reconfigurable switched-capacitor DC-DC converter is proposed to convert the unstable supercap's voltage (3.5V~0.5V) to a stable 1V output voltage efficiently to power the subsequent circuits. With the help of the 6 conversion ratios (3 step-ups, 3 step-downs), voltage protection techniques, and low power designs, the converter can extract 98% of the stored energy from the supercap, and increase initial energy by 96%. Another switched-inductor buck-boost converter is designed to harvest the ambient RF energy to charge the supercap quickly. Because of the variation of the reader distance and incident wave angle, the input power level also has large fluctuation (5uW~5mW). The harvester handles this large power range by a power estimator enhanced MPPT controller with an adaptive integration capacitor array. Also, the contradiction between low power and high tracking speed is improved by adaptive MPPT frequency

Power Management and SRAM for Energy-Autonomous and Low-Power Systems

We demonstrate the two first-known, complete, self-powered millimeter-scale computer systems. These microsystems achieve zero-net-energy operation using solar energy harvesting and ultra-low-power circuits. A medical implant for monitoring intraocular pressure (IOP) is presented as part of a treatment for glaucoma. The 1.5mm3 IOP monitor is easily implantable because of its small size and measures IOP with 0.5mmHg accuracy. It wirelessly transmits data to an external wand while consuming 4.7nJ/bit. This provides rapid feedback about treatment efficacies to decrease physician response time and potentially prevent unnecessary vision loss. A nearly-perpetual temperature sensor is presented that processes data using a 2.1μW near-threshold ARM°R Cortex- M3TM μP that provides a widely-used and trusted programming platform. Energy harvesting and power management techniques for these two microsystems enable energy-autonomous operation. The IOP monitor harvests 80nW of solar power while consuming only 5.3nW, extending lifetime indefinitely. This allows the device to provide medical information for extended periods of time, giving doctors time to converge upon the best glaucoma treatment. The temperature sensor uses on-demand power delivery to improve low-load dc-dc voltage conversion efficiency by 4.75x. It also performs linear regulation to deliver power with low noise, improved load regulation, and tight line regulation. Low-power high-throughput SRAM techniques help millimeter-scale microsystems meet stringent power budgets. VDD scaling in memory decreases energy per access, but also decreases stability margins. These margins can be improved using sizing, VTH selection, and assist circuits, as well as new bitcell designs. Adaptive Crosshairs modulation of SRAM power supplies fixes 70% of parametric failures. Half-differential SRAM design improves stability, reducing VMIN by 72mV. The circuit techniques for energy autonomy presented in this dissertation enable millimeter-scale microsystems for medical implants, such as blood pressure and glucose sensors, as well as non-medical applications, such as supply chain and infrastructure monitoring. These pervasive sensors represent the continuation of Bell’s Law, which accurately traces the evolution of computers as they become smaller, more numerous, and more powerful. The development of millimeter-scale massively-deployed ubiquitous computers ensures the continued expansion and profitability of the semiconductor industry. NanoWatt circuit techniques will allow us to meet this next frontier in IC design.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86387/1/grgkchen_1.pd

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

Design of Low-Cost Energy Harvesting and Delivery Systems for Self-Powered Devices: Application to Authentication IC

This thesis investigates the development of low-cost energy harvesting and delivery systems for low-power low-duty-cycle devices. Initially, we begin by designing a power management scheme for on-demand power delivery. The baseline implementation is also used to identify critical challenges for low-power energy harvesting. We further propose a robust self-powered energy harvesting and delivery system (EHDS) design as a solution to achieve energy autonomy in standalone systems. The design demonstrates a complete ecosystem for low-overhead pulse-frequency modulated (PFM) harvesting while reducing harvesting window confinement and overall implementation footprint. Two transient-based models are developed for improved accuracy during design space exploration and optimization for both PFM power conversion and energy harvesting. Finally, a low-power authentication IC is demonstrated and projected designs for self-powered System-on-Chips (SoCs) are presented. The proposed designs are proto-typed in two test-chips in a 65nm CMOS process and measurement data showcase improved performance in terms of battery power, cold-start duration, passives (inductance and capacitance) needed, and end-to-end harvesting/conversion efficiency.Ph.D

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