Towards Optimal Kinetic Energy Harvesting for the Batteryless IoT

Traditional Internet of Things (IoT) sensors rely on batteries that need to be replaced or recharged frequently which impedes their pervasive deployment. A promising alternative is to employ energy harvesters that convert the environmental energy into electrical energy. Kinetic Energy Harvesting (KEH) converts the ambient motion/vibration energy into electrical energy to power the IoT sensor nodes. However, most previous works employ KEH without dynamically tracking the optimal operating point of the transducer for maximum power output. In this paper, we systematically analyse the relation between the operating point of the transducer and the corresponding energy yield. To this end, we explore the voltage-current characteristics of the KEH transducer to find its Maximum Power Point (MPP). We show how this operating point can be approximated in a practical energy harvesting circuit. We design two hardware circuit prototypes to evaluate the performance of the proposed mechanism and analyse the harvested energy using a precise load shaker under a wide set of controlled conditions typically found in human-centric applications. We analyse the dynamic current-voltage characteristics and specify the relation between the MPP sampling rate and harvesting efficiency which outlines the need for dynamic MPP tracking. The results show that the proposed energy harvesting mechanism outperforms the conventional method in terms of generated power and offers at least one order of magnitude higher power than the latter

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

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

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

Design considerations of sub-mW indoor light energy harvesting for wireless sensor systems

For most wireless sensor networks, one common and major bottleneck is the limited battery lifetime. The frequent maintenance efforts associated with battery replacement significantly increase the system operational and logistics cost. Unnoticed power failures on nodes will degrade the system reliability and may lead to system failure. In building management applications, to solve this problem, small energy sources such as indoor light energy are promising to provide long-term power to these distributed wireless sensor nodes. This paper provides comprehensive design considerations for an indoor light energy harvesting system for building management applications. Photovoltaic cells characteristics, energy storage units, power management circuit design and power consumption pattern of the target mote are presented. Maximum power point tracking circuits are proposed which significantly increase the power obtained from the solar cells. The novel fast charge circuit reduces the charging time. A prototype was then successfully built and tested in various indoor light conditions to discover the practical issues of the design. The evaluation results show that the proposed prototype increases the power harvested from the PV cells by 30% and also accelerates the charging rate by 34% in a typical indoor lighting condition. By entirely eliminating the rechargeable battery as energy storage, the proposed system would expect an operational lifetime 10-20 years instead of the current less than 6 months battery lifetim

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

Analysis and optimal design of micro-energy harvesting systems for wireless sensor nodes

Presently, wireless sensor nodes are widely used and the lifetime of the system is becoming the biggest problem with using this technology. As more and more low power products have been used in WSN, energy harvesting technologies, based on their own characteristics, attract more and more attention in this area. But in order to design high energy efficiency, low cost and nearly perpetual lifetime micro energy harvesting system is still challenging. This thesis proposes a new way, by applying three factors of the system, which are the energy generation, the energy consumption and the power management strategy, into a theoretical model, to optimally design a highly efficient micro energy harvesting system in a real environment. In order to achieve this goal, three aspects of contributions, which are theoretically analysis an energy harvesting system, practically enhancing the system efficiency, and real system implementation, have been made. For the theoretically analysis, the generic architecture and the system design procedure have been proposed to guide system design. Based on the proposed system architecture, the theoretical analytical models of solar and thermal energy harvesting systems have been developed to evaluate the performance of the system before it being designed and implemented. Based on the model’s findings, two approaches (MPPT based power conversion circuit and the power management subsystem) have been considered to practically increase the system efficiency. As this research has been funded by the two public projects, two energy harvesting systems (solar and thermal) powered wireless sensor nodes have been developed and implemented in the real environments based on the proposed work, although other energy sources are given passing treatment. The experimental results show that the two systems have been efficiently designed with the optimization of the system parameters by using the simulation model. The further experimental results, tested in the real environments, show that both systems can have nearly perpetual lifetime with high energy efficiency

A Survey of Energy Harvesting Sources for IoT Device

Environmental Energy is an alternative energy for wireless devices. A Survey of Energy Harvesting Sources for IoT Device is proposed. This paper identifies the sources of energy harvesting, methods and power density of each technique. Many reassert have carried to extract energy from environment. The IoT and M2M are connected through internet or local area network and these devices come with batteries. The maintenance and charging of batteries becomes tedious due to thousands of device are connected. The concept of Energy harvesting gives the solution for powering IoT, M2M, Wireless nodes etc. The process of extracting energy from the surrounding environment is termed as energy harvesting and derived from windmill and water wheel, thermal, mechanical, solar

Maximum power point tracking CMOS circuit to connect a solar cell into a solid-state battery

This paper presents a Maximum Power Point Tracking (MPPT) circuit in CMOS technology for integration into an energy harvesting solution, comprising a solid-state thin-film lithium battery fabricated in the back side of a plastic solar cell. The MPPT CMOS circuit is required in the energy transfer process from the solar cell to the battery. The MPPT circuit was designed in the 0.7 µm CMOS process from on semiconductor (former AMIS, Alcatel-Mietec). The pulse width modulation (PWM) gate control of the DC-DC step-up converter is obtained only with analog circuits, which are composed by rail-to-rail operational amplifiers, analog multipliers and a ring oscillator. The ripple correlation control algorithm is used in the implementation of the analog MPPT circuit. This is a dynamically rapid method (e.g., 5 ms step response was measured) where the inevitable ripple of the inductor current of the DC-DC converter is analyzed and used to adjust the set-point of the same DC-DC converter. The full energy harvesting is also described in this paper