A fully integrated autonomous power management system with high power capacity and novel MPPT for thermoelectric energy harvesters in IoT/wearable applications

This paper reports a fully integrated autonomous power management system for thermoelectric energy harvesting with application in batteryless IoT/Wearable devices. The novel maximum power point tracking (MPPT) algorithm does not require open circuit voltage measurement. The proposed system delivers 0.5 mA current with 1 V regulated output based on simulations, which is the highest output current for a fully integrated converter reported in the literature for ultra-low voltage applications, to the best knowledge of the authors. Regulated 1 V output can be achieved for load range >2 k Omega, and input voltage range >140 mV. The circuit has been implemented in UMC-180nm standard CMOS technology and simulated

Strategies and Techniques for Powering Wireless Sensor Nodes through Energy Harvesting and Wireless Power Transfer

The continuous development of the internet of things (IoT) infrastructure and applications is paving the way for advanced and innovative ideas and solutions, some of which are pushing the limits of state-of-the-art technology. The increasing demand for Wireless Sensor Nodes (WSNs) able to collect and transmit data through wireless communication channels, while often positioned in locations that are difficult to access, is driving research into innovative solutions involving energy harvesting (EH) and wireless power transfer (WPT) to eventually allow battery-free sensor nodes. Due to the pervasiveness of radio frequency (RF) energy, RF EH and WPT are key technologies with the potential to power IoT devices and smart sensing architectures involving nodes that need to be wireless, maintenance free, and sufficiently low in cost to promote their use almost anywhere. This paper presents a state-of-the-art, ultra-low power 2.5 W highly integrated mixed-signal system on chip (SoC), for multi-source energy harvesting and wireless power transfer. It introduces a novel architecture that integrates an ultra-low power intelligent power management, an RF to DC converter with very low power sensitivity and high power conversion efficiency (PCE), an Amplitude-Shift-Keying/Frequency-Shift-Keying (ASK/FSK) receiver and digital circuitry to achieve the advantage to cope, in a versatile way and with minimal use of external components, with the wide variety of energy sources and use cases. Diverse methods for powering wireless Sensor Nodes through energy harvesting and wireless power transfer are implemented providing related system architectures and experimental results

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

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

Embedded Trusted Monitoring and Management Modules for Smart Solar Panels

This paper investigates developing a prototype of smart solar panels. This architecture consists of a panel monitoring module and the central management unit. The monitoring module is to be embedded inside each PV panel making it secure to transfer the trusted data via Wi-Fi to the central Management unit (which can accommodate an array of PV panels in an installation). This module is required for data storage and provides the ability to upload secure data to the cloud. This platform presents the ability to securely manage large numbers of rooftop solar panels in a distributed ledger by implementing block chain algorithm. For achieving this purpose, Module 400 is envisaged to be turned into a Blockchain node as it provides the infrastructure to implement this technology

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

Internet of Things Strategic Research Roadmap

Internet of Things (IoT) is an integrated part of Future Internet including existing and evolving Internet and network developments and could be conceptually defined as a dynamic global network infrastructure with self configuring capabilities based on standard and interoperable communication protocols where physical and virtual “things” have identities, physical attributes, and virtual personalities, use intelligent interfaces, and are seamlessly integrated into the information network