Survey of Energy Harvesting Technologies for Wireless Sensor Networks

Energy harvesting (EH) technologies could lead to self-sustaining wireless sensor networks (WSNs) which are set to be a key technology in Industry 4.0. There are numerous methods for small-scale EH but these methods differ greatly in their environmental applicability, energy conversion characteristics, and physical form which makes choosing a suitable EH method for a particular WSN application challenging due to the specific application-dependency. Furthermore, the choice of EH technology is intrinsically linked to non-trivial decisions on energy storage technologies and combinatorial architectures for a given WSN application. In this paper we survey the current state of EH technology for small-scale WSNs in terms of EH methods, energy storage technologies, and EH system architectures for combining methods and storage including multi-source and multi-storage architectures, as well as highlighting a number of other optimisation considerations. This work is intended to provide an introduction to EH technologies in terms of their general working principle, application potential, and other implementation considerations with the aim of accelerating the development of sustainable WSN applications in industry

Energy Harvesting Systems for the Internet of Things with Applications to Smart Agriculture

The Internet of Things is the interconnection of everyday objects to the web, with the purpose of exchanging information to enable smarter actions and potentially make a process more efficient. However, how power is provided and stored in remote sensing applications is still one of the main modern electronics challenges of such technology and can become one of the main constraints to prevent its mass adoption. Energy Harvesting is an emerging technology that can transform energy in the environment into usable energy, among such environmental energy are electromagnetic waves, thermal, solar, kinesthetic transducers, fuel cells, to name a few. Because this technology makes use of the available ambient energy, it has the potential to increase the power readiness for battery-operated electronics and more importantly, it can become the technology that fully powers the next generation of internet-enabled agricultural solutions. This dissertation centers around the design and development of high-efficient power management systems for AC and DC energy harvesting sources. The proposed architectures not only consider circuits, systems and algorithms that make a more efficient power extraction but also focuses on providing inherent sensing functionalities at no extra system complexity, which in turn not only achieves the goal of extending the battery life of proposed smart sensor applications but also proposes new charge extraction methods to permanently power an electronic device. The work presented in this dissertation demonstrates that energy harvesting, and internet of things devices can be implemented in multiple smart agriculture scenarios by proposing algorithms, circuits and systems capable of performing energy harvesting operations while providing reliable data to the end user. The analysis of the design of such proof-of-concept prototypes are provided in this dissertation along with its implementation and testing. The first part of this dissertation proposes novel algorithms for maximum power extraction and new power measurement techniques. The second part focuses on front-end circuits for AC energy harvesting sources and circuits that can provide sensing capabilities along with energy harvesting operations

Towards persistent structural health monitoring through sustainable wireless sensor networks

This paper documents the design, implementation and characterisation of a wireless sensor node (GENESI Node v1.0), applicable to long-term structural health monitoring. Presented is a three layer abstraction of the hardware platform; consisting of a Sensor Layer, a Main Layer and a Power Layer. Extended operational lifetime is one of the primary design goals, necessitating the inclusion of supplemental energy sources, energy awareness, and the implementation of optimal components (microcontroller(s), RF transceiver, etc.) to achieve lowest-possible power consumption, whilst ensuring that the functional requirements of the intended application area are satisfied. A novel Smart Power Unit has been developed; including intelligence, ambient available energy harvesting (EH), storage, electrochemical fuel cell integration, and recharging capability, which acts as the Power Layer for the node. The functional node has been prototyped, demonstrated and characterised in a variety of operational modes. It is demonstrable via simulation that, under normal operating conditions within a structural health monitoring application, the node may operate perpetually

Design of a Multi-sensor and Re-configurable Smart Node for the IoT

The rapid deployment of the Internet of Things (IoT) is much dependent on the capacity of the IoT node to be able to self-adapt to the target application. With the increase of sensor networks and diversity of sensors available and with the increasing integration of multiple sensors in a sensor node, it is necessary to develop systems capable of handling all of these sensors with high level of flexibility. These may have different characteristics that provide quite distinct interface requirements, thus giving rise to the need for systems with re-configurable properties. With the implementation of sensor networks in places where energy supply is limited or non-existent, and in situations where technician intervention is expensive, there is a need to exchange conventional energy sources by methods of storage and harvesting of the energy present in the environment, where the sensor node is used (autonomous and renewable energy sources). This thesis will focus on the study and implementation of a family of re-configurable and multi-sensor IoT nodes with special emphasis on the energy storage and power management. It will also focus on the develop of a CAD tool in order to help in the design of CMOS circuits, for the purpose of integrating all the strategies here presented

Power Management ICs for Internet of Things, Energy Harvesting and Biomedical Devices

This dissertation focuses on the power management unit (PMU) and integrated circuits (ICs) for the internet of things (IoT), energy harvesting and biomedical devices. Three monolithic power harvesting methods are studied for different challenges of smart nodes of IoT networks. Firstly, we propose that an impedance tuning approach is implemented with a capacitor value modulation to eliminate the quiescent power consumption. Secondly, we develop a hill-climbing MPPT mechanism that reuses and processes the information of the hysteresis controller in the time-domain and is free of power hungry analog circuits. Furthermore, the typical power-performance tradeoff of the hysteresis controller is solved by a self-triggered one-shot mechanism. Thus, the output regulation achieves high-performance and yet low-power operations as low as 12 µW. Thirdly, we introduce a reconfigurable charge pump to provide the hybrid conversion ratios (CRs) as 1⅓× up to 8× for minimizing the charge redistribution loss. The reconfigurable feature also dynamically tunes to maximum power point tracking (MPPT) with the frequency modulation, resulting in a two-dimensional MPPT. Therefore, the voltage conversion efficiency (VCE) and the power conversion efficiency (PCE) are enhanced and flattened across a wide harvesting range as 0.45 to 3 V. In a conclusion, we successfully develop an energy harvesting method for the IoT smart nodes with lower cost, smaller size, higher conversion efficiency, and better applicability. For the biomedical devices, this dissertation presents a novel cost-effective automatic resonance tracking method with maximum power transfer (MPT) for piezoelectric transducers (PT). The proposed tracking method is based on a band-pass filter (BPF) oscillator, exploiting the PT’s intrinsic resonance point through a sensing bridge. It guarantees automatic resonance tracking and maximum electrical power converted into mechanical motion regardless of process variations and environmental interferences. Thus, the proposed BPF oscillator-based scheme was designed for an ultrasonic vessel sealing and dissecting (UVSD) system. The sealing and dissecting functions were verified experimentally in chicken tissue and glycerin. Furthermore, a combined sensing scheme circuit allows multiple surgical tissue debulking, vessel sealer and dissector (VSD) technologies to operate from the same sensing scheme board. Its advantage is that a single driver controller could be used for both systems simplifying the complexity and design cost. In a conclusion, we successfully develop an ultrasonic scalpel to replace the other electrosurgical counterparts and the conventional scalpels with lower cost and better functionality

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

Energy Harvesting Techniques for Internet of Things (IoT)

The rapid growth of the Internet of Things (IoT) has accelerated strong interests in the development of low-power wireless sensors. Today, wireless sensors are integrated within IoT systems to gather information in a reliable and practical manner to monitor processes and control activities in areas such as transportation, energy, civil infrastructure, smart buildings, environment monitoring, healthcare, defense, manufacturing, and production. The long-term and self-sustainable operation of these IoT devices must be considered early on when they are designed and implemented. Traditionally, wireless sensors have often been powered by batteries, which, despite allowing low overall system costs, can negatively impact the lifespan and the performance of the entire network they are used in. Energy Harvesting (EH) technology is a promising environment-friendly solution that extends the lifetime of these sensors, and, in some cases completely replaces the use of battery power. In addition, energy harvesting offers economic and practical advantages through the optimal use of energy, and the provisioning of lower network maintenance costs. We review recent advances in energy harvesting techniques for IoT. We demonstrate two energy harvesting techniques using case studies. Finally, we discuss some future research challenges that must be addressed to enable the large-scale deployment of energy harvesting solutions for IoT environments

A miniaturised autonomous sensor based on nanowire materials platform: the SiNAPS mote

A micro-power energy harvesting system based on core(crystalline Si)-shell(amorphous Si) nanowire solar cells together with a nanowire-modified CMOS sensing platform have been developed to be used in a dust-sized autonomous chemical sensor node. The mote (SiNAPS) is augmented by low-power electronics for power management and sensor interfacing, on a chip area of 0.25mm2. Direct charging of the target battery (e.g., NiMH microbattery) is achieved with end-to-end efficiencies up to 90% at AM1.5 illumination and 80% under 100 times reduced intensity. This requires matching the voltages of the photovoltaic module and the battery circumventing maximum power point tracking. Single solar cells show efficiencies up to 10% under AM1.5 illumination and open circuit voltages, Voc, of 450-500mV. To match the battery’s voltage the miniaturised solar cells (~1mm2 area) are connected in series via wire bonding. The chemical sensor platform (mm2 area) is set up to detect hydrogen gas concentration in the low ppm range and over a broad temperature range using a low power sensing interface circuit. Using Telran TZ1053 radio to send one sample measurement of both temperature and H2 concentration every 15 seconds, the average and active power consumption for the SiNAPS mote are less than 350nW and 2.1 μW respectively. Low-power miniaturised chemical sensors of liquid analytes through microfluidic delivery to silicon nanowires are also presented. These components demonstrate the potential of further miniaturization and application of sensor nodes beyond the typical physical sensors, and are enabled by the nanowire materials platform