Wind energy harvester interface for sensor nodes

The research topic is developping a power converting interface for the novel FLEHAP wind energy harvester allowing the produced energy to be used for powering small wireless nodes. The harvester\u2019s electrical characteristics were studied and a strategy was developped to control and mainting a maximum power transfer. The electronic power converter interface was designed, containing an AC/DC Buck-Boost converter and controlled with a low power microcontroller. Different prototypes were developped that evolved by reducing the sources of power loss and rendering the system more efficient. The validation of the system was done through simulations in the COSMIC/DITEN lab using generated signals, and then follow-up experiments were conducted with a controllable wind tunnel in the DIFI department University of Genoa. The experiment results proved the functionality of the control algorithm as well as the efficiency that was ramped up by the hardware solutions that were implemented, and generally met the requirement to provide a power source for low-power 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

Low-Power Energy Efficient Circuit Techniques for Small IoT Systems

Although the improvement in circuit speed has been limited in recent years, there has been increased focus on the internet of things (IoT) as technology scaling has decreased circuit size, power usage and cost. This trend has led to the development of many small sensor systems with affordable costs and diverse functions, offering people convenient connection with and control over their surroundings. This dissertation discusses the major challenges and their solutions in realizing small IoT systems, focusing on non-digital blocks, such as power converters and analog sensing blocks, which have difficulty in following the traditional scaling trends of digital circuits. To accommodate the limited energy storage and harvesting capacity of small IoT systems, this dissertation presents an energy harvester and voltage regulators with low quiescent power and good efficiency in ultra-low power ranges. Switched-capacitor-based converters with wide-range energy-efficient voltage-controlled oscillators assisted by power-efficient self-oscillating voltage doublers and new cascaded converter topologies for more conversion ratio configurability achieve efficient power conversion down to several nanowatts. To further improve the power efficiency of these systems, analog circuits essential to most wireless IoT systems are also discussed and improved. A capacitance-to-digital sensor interface and a clocked comparator design are improved by their digital-like implementation and operation in phase and frequency domain. Thanks to the removal of large passive elements and complex analog blocks, both designs achieve excellent area reduction while maintaining state-of-art energy efficiencies. Finally, a technique for removing dynamic voltage and temperature variations is presented as smaller circuits in advanced technologies are more vulnerable to these variations. A 2-D simultaneous feedback control using an on-chip oven control locks the supply voltage and temperature of a small on-chip domain and protects circuits in this locked domain from external voltage and temperature changes, demonstrating 0.0066 V/V and 0.013 °C/°C sensitivities to external changes. Simple digital implementation of the sensors and most parts of the control loops allows robust operation within wide voltage and temperature ranges.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138743/1/wanyeong_1.pd

Piezoelectric Energy Harvesting: Enhancing Power Output by Device Optimisation and Circuit Techniques

Energy harvesting; that is, harvesting small amounts of energy from environmental sources such as solar, air flow or vibrations using small-scale (≈1cm 3 ) devices, offers the prospect of powering portable electronic devices such as GPS receivers and mobile phones, and sensing devices used in remote applications: wireless sensor nodes, without the use of batteries. Numerous studies have shown that power densities of energy harvesting devices can be hundreds of µW; however the literature also reveals that power requirements of many electronic devices are in the mW range. Therefore, a key challenge for the successful deployment of energy harvesting technology remains, in many cases, the provision of adequate power. This thesis aims to address this challenge by investigating two methods of enhancing the power output of a piezoelectric-based vibration energy harvesting device. Cont/d

Double smart energy harvesting system for self-powered industrial IoT

312 p. 335 p. (confidencial)Future factories would be based on the Industry 4.0 paradigm. IndustrialInternet of Things (IIoT) represent a part of the solution in this field. Asautonomous systems, powering challenges could be solved using energy harvestingtechnology. The present thesis work combines two alternatives of energy input andmanagement on a single architecture. A mini-reactor and an indoor photovoltaiccell as energy harvesters and a double power manager with AC/DC and DC/DCconverters controlled by a low power single controller. Furthermore, theaforementioned energy management is improved with artificial intelligencetechniques, which allows a smart and optimal energy management. Besides, theharvested energy is going to be stored in a low power supercapacitor. The workconcludes with the integration of these solutions making IIoT self-powered devices.IK4 Teknike

Wireless communication over NFC with a constrained resouce device

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201

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

Measurement Of The Electric Energy Storage Capacity In Solar Thermoelectric Generators' Energy Harvesting Modules

Reducing energy consumption is mandatory in self-powered sensor nodes of wireless sensor networks that obtain all their energy from the environment. In this direction, one first step to optimize the network is to accurately measure the total energy harvested, which will determine the power available for sensor consumption. We present here a technique based on an embedded circuit with an ultra-low-power microcontroller to accurately measure the efficiency of flat-panel solar thermoelectric generators operating with environmental temperature gradients. Experimental tests showed that when a voltage of 180 mV (best case in an environmental flat-panel solar thermoelectric generators) is applied to the input of the DC-DC converter, the proposed technique eliminates a measurement error of 33% when compared with the conventional single supercapacitor strategy.13

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

Hybrid Energy Harvesting for Self Powered Human Applications

Continuing progress in reduction of size and power consumption of semiconductors, and significant improvement in their capability to compute sense and communicate data, have enabled a new area of wearable electronics and smart garments. Mobile electronics devices such as smart phones, tablets, laptops, e-readers and GPS devices have shaped and defined the world of consumer electronics. As such those devices interact with us on every day level, keeping us connected with environment through the use of sensors, imagers, location based services and data networks. Looking beyond typical consumer applications, there is an increasing demand for a wearable and energy efficient electronics capable of operating from human harvested energy. This study will present a solution that is capable of providing basic human bio-parametric data such as: body temperature, pressure, man down indication, impact occurrence indication as well as data on orientation and inclination. All those functions will be embedded as wearable electronics and be able to operate from the energy that was harvested from human body. The need to have this kind of data collected on the human subject in especially demanding environments and situations is greatly appreciative in applications related to search and rescue agencies, paramedics, firefighters and security and police. The solution presented in this thesis is focusing on energy harvesting from human body and the environment, together with utilization of such energy for wearable electronic