Energy autonomous systems : future trends in devices, technology, and systems

The rapid evolution of electronic devices since the beginning of the nanoelectronics era has brought about exceptional computational power in an ever shrinking system footprint. This has enabled among others the wealth of nomadic battery powered wireless systems (smart phones, mp3 players, GPS, …) that society currently enjoys. Emerging integration technologies enabling even smaller volumes and the associated increased functional density may bring about a new revolution in systems targeting wearable healthcare, wellness, lifestyle and industrial monitoring applications

Energy challenges for ICT

The energy consumption from the expanding use of information and communications technology (ICT) is unsustainable with present drivers, and it will impact heavily on the future climate change. However, ICT devices have the potential to contribute signi - cantly to the reduction of CO2 emission and enhance resource e ciency in other sectors, e.g., transportation (through intelligent transportation and advanced driver assistance systems and self-driving vehicles), heating (through smart building control), and manu- facturing (through digital automation based on smart autonomous sensors). To address the energy sustainability of ICT and capture the full potential of ICT in resource e - ciency, a multidisciplinary ICT-energy community needs to be brought together cover- ing devices, microarchitectures, ultra large-scale integration (ULSI), high-performance computing (HPC), energy harvesting, energy storage, system design, embedded sys- tems, e cient electronics, static analysis, and computation. In this chapter, we introduce challenges and opportunities in this emerging eld and a common framework to strive towards energy-sustainable ICT

A Charge-Recycling Scheme and Ultra Low Voltage Self-Startup Charge Pump for Highly Energy Efficient Mixed Signal Systems-On-A-Chip

The advent of battery operated sensor-based electronic systems has provided a pressing need to design energy-efficient, ultra-low power integrated circuits as a means to improve the battery lifetime. This dissertation describes a scheme to lower the power requirement of a digital circuit through the use of charge-recycling and dynamic supply-voltage scaling techniques. The novel charge-recycling scheme proposed in this research demonstrates the feasibility of operating digital circuits using the charge scavenged from the leakage and dynamic load currents inherent to digital design. The proposed scheme efficiently gathers the “ground-bound” charge into storage capacitor banks. This reclaimed charge is then subsequently recycled to power the source digital circuit. The charge-recycling methodology has been implemented on a 12-bit Gray-code counter operating at frequencies of less than 50 MHz. The circuit has been designed in a 90-nm process and measurement results reveal more than 41% reduction in the average energy consumption of the counter. The total energy savings including the power consumed for the generation of control signals aggregates to an average of 23%. The proposed methodology can be applied to an existing digital path without any design change to the circuit but with only small loss to the performance. Potential applications of this scheme are described, specifically in wide-temperature dynamic power reduction and as a source for energy harvesters. The second part of this dissertation deals with the design and development of a self-starting, ultra-low voltage, switched-capacitor (SC) DC-DC converter that is essential to an energy harvesting system. The proposed charge-pump based SC-converter operates from 125-mV input and thus enables battery-less operation in ultra-low voltage energy harvesters. The charge pump does not require any external components or expensive post-fabrication processing to enable low-voltage operation. This design has been implemented in a 130-nm CMOS process. While the proposed charge pump provides significant efficiency enhancement in energy harvesters, it can also be incorporated within charge recycling systems to facilitate adaptable charge-recycling levels. In total, this dissertation provides key components needed for highly energy-efficient mixed signal systems-on-a-chip

Energy Harvesting and Energy Storage Systems

This book discuss the recent developments in energy harvesting and energy storage systems. Sustainable development systems are based on three pillars: economic development, environmental stewardship, and social equity. One of the guiding principles for finding the balance between these pillars is to limit the use of non-renewable energy sources

Waldo: Batteryless Occupancy Monitoring with Reflected Ambient Light

Reliable and accurate room-level occupancy-tracking systems can enable many new advances in sensors and applications of modern smart buildings. This allows buildings to be more capable of adapting to the needs of their occupants in their day-to-day activities and better optimize certain resources, such as power and air conditioning, to do so. Unfortunately, existing occupancy-tracking systems are plagued by large size, high energy consumption, and, unsurprisingly, short battery lifetimes. In this paper, we present Waldo, a batteryless, room-level occupancy monitoring sensor that harvests energy from indoor ambient light reflections, and uses changes in these reflections to detect when people enter and exit a room. Waldo is mountable at the top of a doorframe, allowing for detection of a person and the direction they are traveling at the entry and exit point of a room. We evaluated the Waldo sensor in an office-style setting under mixed lighting conditions (natural and artificial) on both sides of the doorway with subjects exhibiting varying physical characteristics such as height, hair color, gait, and clothing. 651 number of controlled experiments were ran on 6 doorways with 12 individuals and achieved a total detection accuracy of 97.38%. Further, it judged the direction of movement correctly with an accuracy of 95.42%. This paper also evaluates and discusses various practical factors that can impact the performance of the current system in actual deployments. This work demonstrates that ambient light reflections provide both a promising low-cost, long-term sustainable option for monitoring how people use buildings and an exciting new research direction for batteryless computing

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

Sophisticated Batteryless Sensing

Wireless embedded sensing systems have revolutionized scientific, industrial, and consumer applications. Sensors have become a fixture in our daily lives, as well as the scientific and industrial communities by allowing continuous monitoring of people, wildlife, plants, buildings, roads and highways, pipelines, and countless other objects. Recently a new vision for sensing has emerged---known as the Internet-of-Things (IoT)---where trillions of devices invisibly sense, coordinate, and communicate to support our life and well being. However, the sheer scale of the IoT has presented serious problems for current sensing technologies---mainly, the unsustainable maintenance, ecological, and economic costs of recycling or disposing of trillions of batteries. This energy storage bottleneck has prevented massive deployments of tiny sensing devices at the edge of the IoT. This dissertation explores an alternative---leave the batteries behind, and harvest the energy required for sensing tasks from the environment the device is embedded in. These sensors can be made cheaper, smaller, and will last decades longer than their battery powered counterparts, making them a perfect fit for the requirements of the IoT. These sensors can be deployed where battery powered sensors cannot---embedded in concrete, shot into space, or even implanted in animals and people. However, these batteryless sensors may lose power at any point, with no warning, for unpredictable lengths of time. Programming, profiling, debugging, and building applications with these devices pose significant challenges. First, batteryless devices operate in unpredictable environments, where voltages vary and power failures can occur at any time---often devices are in failure for hours. Second, a device\u27s behavior effects the amount of energy they can harvest---meaning small changes in tasks can drastically change harvester efficiency. Third, the programming interfaces of batteryless devices are ill-defined and non- intuitive; most developers have trouble anticipating the problems inherent with an intermittent power supply. Finally, the lack of community, and a standard usable hardware platform have reduced the resources and prototyping ability of the developer. In this dissertation we present solutions to these challenges in the form of a tool for repeatable and realistic experimentation called Ekho, a reconfigurable hardware platform named Flicker, and a language and runtime for timely execution of intermittent programs called Mayfly

Model-based design for self-sustainable sensor nodes

Long-term and maintenance-free operation is a critical feature for large-scale deployed battery-operated sensor nodes. Energy harvesting (EH) is the most promising technology to overcome the energy bottleneck of today’s sensors and to enable the vision of perpetual operation. However, relying on fluctuating environmental energy requires an application-specific analysis of the energy statistics combined with an in-depth characterization of circuits and algorithms, making design and verification complex. This article presents a model-based design (MBD) approach for EH-enabled devices accounting for the dynamic behavior of components in the power generation, conversion, storage, and discharge paths. The extension of existing compact models combined with data-driven statistical modeling of harvesting circuits allows accurate offline analysis, verification, and validation. The presented approach facilitates application-specific optimization during the development phase and reliable long-term evaluation combined with environmental datasets. Experimental results demonstrate the accuracy and flexibility of this approach: the model verification of a solar-powered wireless sensor node shows a determination coefficient () of 0.992, resulting in an energy error of only -1.57 % between measurement and simulation. Compared to state-of-practice methods, the MBD approach attains a reduction of the estimated state-of-charge error of up to 10.2 % in a real-world scenario. MBD offers non-trivial insights on critical design choices: the analysis of the storage element selection reveals a 2–3 times too high self-discharge per capacity ratio for supercapacitors and a peak current constrain for lithium-ion polymer batteries

Numerical and experimental performance study of two-degrees-of-freedom electromagnetic energy harvesters

Energy harvesting is a rising technology able to replace conventional batteries in supplying low-power devices. Researchers are studying the use of energy harvesters in Autonomous Internet of Things (AIoT) systems to create a wireless network of nodes for real-time monitoring of assets. Electromagnetic energy harvesters exploiting ambient vibrations for electric power generation are used in monitoring applications for sensorized industrial vehicles or mechanical systems. This paper shows a design methodology for two-degrees-of-freedom gravitational electromagnetic energy harvesters (2DOF GEMEHs) along with prototype testings. The main purpose of this non-linear two-degrees-of-freedom system is to improve conversion efficiency and bandwidth broadening through the introduction of a second resonance frequency. The proposed harvester devices could be suited for vehicle monitoring and in particular railway monitoring applications. The novelty of the configuration is the use of two magnetic springs and the series connection of two induction coils. The system design achieves long-lasting performances since there are no mechanical parts involved in the dynamics, thus being compatible with low maintenance requirements. 2DOF GEMEHs can have the two resonance frequencies tuned to two fundamental frequencies of the vehicle harvested vibrations for power enhancement. Infreight trains applications the system resonance frequencies may be tuned to the two natural frequencies of the bogie when the railcar is in tare and loaded conditions. The working principle, configuration and analytical model of these devices are described in a detailed way. The numerical modeling approach consists of a combination of FEM analyses in Ansys Maxwell and dynamic simulations in Simulink for evaluation of stiffness and damping characteristics of the system. Experimental laboratory tests on harvester prototypes are compared to numerical results of dynamic simulations for the validation of the proposed model through error estimation. Performance improvements of the 2DOF GEMEH are evaluated through the definition of a merit factor based on output power and bandwidth. The use of a 2DOFsystem is justified by comparing its efficiency respect to the 1DOF configuration, leading to an overall harvesting performance improvement of 10%