Supercapacitor leakage in energy-harvesting sensor nodes: fact or fiction?

As interest in energy-harvesting sensor nodes continues to grow, the use of supercapacitors as energy stores or buffers is gaining popularity. The reasons for their use are numerous, and include their high power density, simple interfacing requirements, simpler measurement of state-of-charge, and a greater number of charging cycles than secondary batteries. However, supercapacitor energy densities are orders of magnitude lower. Furthermore, they have been reported to exhibit significant leakage, and this has been shown to increase exponentially with terminal voltage (and hence stored energy). This observation has resulted in a number of algorithms, designs and methods being proposed for effective operation of supercapacitor-based energy-harvesting sensor nodes. In this paper, it is argued that traditional ‘leakage’ is not as significant as has commonly been suggested. Instead, what is observed as leakage is in fact predominantly due to internal charge redistribution. As a result, it is suggested that different approaches are required in order to effectively utilize supercapacitors in energy-harvesting sensor nodes

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

Towards self-powered wireless sensor networks

Ubiquitous computing aims at creating smart environments in which computational and communication capabilities permeate the word at all scales, improving the human experience and quality of life in a totally unobtrusive yet completely reliable manner. According to this vision, an huge variety of smart devices and products (e.g., wireless sensor nodes, mobile phones, cameras, sensors, home appliances and industrial machines) are interconnected to realize a network of distributed agents that continuously collect, process, share and transport information. The impact of such technologies in our everyday life is expected to be massive, as it will enable innovative applications that will profoundly change the world around us. Remotely monitoring the conditions of patients and elderly people inside hospitals and at home, preventing catastrophic failures of buildings and critical structures, realizing smart cities with sustainable management of traffic and automatic monitoring of pollution levels, early detecting earthquake and forest fires, monitoring water quality and detecting water leakages, preventing landslides and avalanches are just some examples of life-enhancing applications made possible by smart ubiquitous computing systems. To turn this vision into a reality, however, new raising challenges have to be addressed, overcoming the limits that currently prevent the pervasive deployment of smart devices that are long lasting, trusted, and fully autonomous. In particular, the most critical factor currently limiting the realization of ubiquitous computing is energy provisioning. In fact, embedded devices are typically powered by short-lived batteries that severely affect their lifespan and reliability, often requiring expensive and invasive maintenance. In this PhD thesis, we investigate the use of energy-harvesting techniques to overcome the energy bottleneck problem suffered by embedded devices, particularly focusing on Wireless Sensor Networks (WSNs), which are one of the key enablers of pervasive computing systems. Energy harvesting allows to use energy readily available from the environment (e.g., from solar light, wind, body movements, etc.) to significantly extend the typical lifetime of low-power devices, enabling ubiquitous computing systems that can last virtually forever. However, the design challenges posed both at the hardware and at the software levels by the design of energy-autonomous devices are many. This thesis addresses some of the most challenging problems of this emerging research area, such as devising mechanisms for energy prediction and management, improving the efficiency of the energy scavenging process, developing protocols for harvesting-aware resource allocation, and providing solutions that enable robust and reliable security support. %, including the design of mechanisms for energy prediction and management, improving the efficiency of the energy harvesting process, the develop of protocols for harvesting-aware resource allocation, and providing solutions that enable robust and reliable security support

On-chip electrochemical capacitors and piezoelectric energy harvesters for self-powering sensor nodes

On-chip sensing and communications in the Internet of things platform have benefited from the miniaturization of faster and low power complementary-metal-oxide semiconductor (CMOS) microelectronics. Micro-electromechanical systems technology (MEMS) and development of novel nanomaterials have further improved the performance of sensors and transducers while also demonstrating reduction in size and power consumption. Integration of such technologies can enable miniaturized nodes to be deployed to construct wireless sensor networks for autonomous data acquisition. Their longevity, however, is determined by the lifetime of the power supply. Traditional batteries cannot fully fulfill the demands of sensor nodes that require long operational duration. Thus, we require solutions that produce their own electricity from the surroundings and store them for future utility. Furthermore, manufacturing of such a power supply must be compatible with CMOS and MEMS technology. In this thesis, we will describe on-chip electrochemical capacitors and piezoelectric energy harvesters as components of such a self-powered sensor node. Our piezoelectric microcantilevers confirm the feasibility of fabricating micro electro-mechanical-systems (MEMS) size two-degree-of-freedom systems which can address the major issue of small bandwidth of piezoelectric micro-energy harvesters. These devices use a cut-out trapezoidal cantilever beam, limited by its footprint area i.e. a 1 cm$^2$ silicon die, to enhance the stress on the cantilever\u27s free end while reducing the gap remarkably between its first two eigenfrequencies in the 400 - 500 Hz and in the 1 - 2 kHz range. The energy from the M-shaped harvesters could be stored in rGO based on-chip electrochemical capacitors. The electrochemical capacitors are manufactured through CMOS compatible, reproducible, and reliable micromachining processes such as chemical vapor deposition of carbon nanofibers (CNF) and spin coating of graphene oxide based (GO) solutions. The impact of electrode geometry and electrode thickness is studied for CNF based electrodes. Furthermore, we have also demonstrated an improvement in their electrochemical performance and yield of spin coated electrochemical capacitors through surface roughening from iron and chromium nanoparticles. The CVD grown CNF and spin coated rGO based devices are evaluated for their respective trade-offs. Finally, to improve the energy density and demonstrate the versatility of the spin coating process, we manufactured electrochemical capacitors from various GO based composites with functional groups heptadecan-9-amine and octadecanamine. The materials were used as a stack to demonstrate high energy density for spin coated electrochemical capacitors. We have also examined the possibility of integrating these devices into a power management unit to fully realize a self-powering on-chip power supply through survey of package fabrication, choice of electrolyte, and device assembly

CMOS indoor light energy harvesting system for wireless sensing applications

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de ComputadoresThis research thesis presents a micro-power light energy harvesting system for indoor environments. Light energy is collected by amorphous silicon photovoltaic (a-Si:H PV) cells, processed by a switched-capacitor (SC) voltage doubler circuit with maximum power point tracking (MPPT), and finally stored in a large capacitor. The MPPT Fractional Open Circuit Voltage (VOC) technique is implemented by an asynchronous state machine (ASM) that creates and, dynamically, adjusts the clock frequency of the step-up SC circuit, matching the input impedance of the SC circuit to the maximum power point (MPP) condition of the PV cells. The ASM has a separate local power supply to make it robust against load variations. In order to reduce the area occupied by the SC circuit, while maintaining an acceptable efficiency value, the SC circuit uses MOSFET capacitors with a charge reusing scheme for the bottom plate parasitic capacitors. The circuit occupies an area of 0.31 mm2 in a 130 nm CMOS technology. The system was designed in order to work under realistic indoor light intensities. Experimental results show that the proposed system, using PV cells with an area of 14 cm2, is capable of starting-up from a 0 V condition, with an irradiance of only 0.32 W/m2. After starting-up, the system requires an irradiance of only 0.18 W/m2 (18 mW/cm2) to remain in operation. The ASM circuit can operate correctly using a local power supply voltage of 453 mV, dissipating only 0.085 mW. These values are, to the best of the authors’ knowledge, the lowest reported in the literature. The maximum efficiency of the SC converter is 70.3% for an input power of 48 mW, which is comparable with reported values from circuits operating at similar power levels.Portuguese Foundation for Science and Technology (FCT/MCTES), under project PEst-OE/EEI/UI0066/2011, and to the CTS multiannual funding, through the PIDDAC Program funds. I am also very grateful for the grant SFRH/PROTEC/67683/2010, financially supported by the IPL – Instituto Politécnico de Lisboa

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

Towards an on-chip power supply: Integration of micro energy harvesting and storage techniques for wireless sensor networks

The lifetime of a power supply in a sensor node of a wireless sensor network is the decisive factor in the longevity of the system. Traditional Li-ion batteries cannot fulfill the demands of sensor networks that require a long operational duration. Thus, we require a solution that produces its own electricity from its surrounding and stores it for future utility. Moreover, as the sensor node architecture is developed on complimentary metal-oxide-semiconductor technology (CMOS), the manufacture of the power supply must be compatible with it. In this thesis, we shall describe the components of an on-chip lifetime power supply that can harvest the vibrational mechanical energy through piezoelectric microcantilevers and store it in a reduced graphene oxide (rGO) based microsupercapacitor, and that is fabricated through CMOS compatible techniques. Our piezoelectric microcantilevers confirm the feasibility of fabricating micro electro- mechanical-systems (MEMS) size two-degree-of-freedom systems which can solve the major issue of small bandwidth of piezoelectric micro-energy harvesters. These devices use a cut-out trapezoidal cantilever beam to enhance the stress on the cantilever’s free end while reducing the gap remarkably between its first two eigenfrequencies in 400 - 500 Hz and 1 - 2 kHz range. The energy from the M-shaped harvesters will be stored in rGO based microsupercapacitors. These microsupercapacitors are manufactured through a fully CMOS compatible, reproducible, and reliable micromachining processes. Furthermore, we have also demonstrated an improvement in their electrochemical performance and yield of fabrication through surface roughening from iron nanoparticles. We have also examined the possibility of integrating these devices into a power management unit to fully realize a lifetime power supply for wireless sensor networks

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 Small Scale Environmentally-Powered Electronic Systems

The continuous advances in integrated circuit fabrication technologies, circuit design, and networking techniques enable the integration of an in-creasing number of functionalities in ever smaller devices. This trend de-termines the multiplication of possible application scenarios for tiny em-bedded systems such as wireless sensors, whose utilization has grown more and more pervasive. However, the operating life time of such sys-tems, when placed in locations not allowing a wired connection to a de-pendable power supply infrastructure, is still heavily limited by the finite capacity of currently available accumulators, whose technology has not improved at the same pace of the electronic systems they supply. Energy harvesting techniques constitute a real solution to power un-tethered computing platforms in this kind of spatially-distributed applica-tions. By converting part of the energy freely available in the surrounding environment to electrical energy, the operating life of the system can be extended considerably, potentially for an unlimited time. In recent years an increasing number of researchers have investigated this possibility. In this dissertation we discuss our results about the study and design of systems capable of harvesting energy from various regenerative sources. We start with the design of an airflow energy harvester, focusing on the optimization of its power generation and efficiency performances, and obtaining superior results with respect to similar works in literature. Then we deal with the improvement of this architecture to implement a fully autonomous vibrational harvester, featuring uncommon in-the-field configuration capabilities. Afterwards we investigate the applicability of self-powered wireless sensor nodes to heavy duty and agricultural machinery, finding attractive vibration sources capable of providing enough power to sustain remarkable data transmission rates. To address remote monitoring applications with stringent needs in terms of power supply availability, we present a truly flexible multi-source energy harvester, along with a simulation framework expressly developed to anticipate the harvester performance when placed in a specific operating environment. Furthermore, the design strategies allowing energy harvesters to fully exploit the locally generated power can be profitably applied in the field of distributed electricity generation from renewable energy sources, to enhance the self-consumption capabilities of microgeneration systems. Based on this motivation, we finally propose a grid-assisted photovoltaic power supply to improve the self-sustainability of ground-source heat pumps, and analyze original data on the consumption profiles of these systems to assess the effectiveness of the design. Energy harvesting techniques have the potential to enable many cut-ting-edge applications, especially in remote sensing and pervasive computing areas, which can bring innovations in several fields of human activity. In this thesis we contribute tackling some of the numerous open research challenges still hampering the widespread adoption of this technology