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

Platform Independent, Illumination aware Reconfigurable Switch Capacitor based 3.3 Volt Energy Harvester IC

This dissertation presents a platform independent illumination aware fully on chip microscale energy harvester for powering 3.3V sensor nodes and smart IOT devices. The programmable switched capacitor DC-DC converter for fully on chip applications is discussed and implemented

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 Circuit Design in Sustainable Self Powered Systems for IoT Applications

The Internet-of-Things (IoT) network is being vigorously pushed forward from many fronts in diverse research communities. Many problems are still there to be solved, and challenges are found among its many levels of abstraction. In this thesis we give an overview of recent developments in circuit design for ultra-low power transceivers and energy harvesting management units for the IoT. The first part of the dissertation conducts a study of energy harvesting interfaces and optimizing power extraction, followed by power management for energy storage and supply regulation. we give an overview of the recent developments in circuit design for ultra-low power management units, focusing mainly in the architectures and techniques required for energy harvesting from multiple heterogeneous sources. Three projects are presented in this area to reach a solution that provides reliable continuous operation for IoT sensor nodes in the presence of one or more natural energy sources to harvest from. The second part focuses on wireless transmission, To reduce the power consumption and boost the Tx energy efficiency, a novel delay cell exploiting current reuse is used in a ring-oscillator employed as the local oscillator generator scheme. In combination with an edge-combiner power amplifier, the Tx showed a measured energy efficiency of 0.2 nJ=bit and a normalized energy efficiency of 3.1 nJ=bit:mW when operating at output power levels up to -10 dBm and data rates of 3 Mbps

Sub 1V Charge Pump based Micro Scale Energy Harvesting for Low Power Application

Harvesting energy from our environment is a promising solution to provide power to wireless sensor network, wearable devices and biomedical implantation. Now a days, usage of battery power system has disappeared because of replacement issues, installation costs every periodic year and the possibility of health hazard in the case of biomedical implants. Considering these issues, energy harvesting proves to be the most feasible and convenient option in the case of wearable devices and biomedical implantation. Hence, we have focused on indoor single solar cell energy harvesting to power ultra-low power load. The tree topology DC-DC converter is used for power management circuit with optimized efficiency. High efficiency is achieved by using ZVT MOSCAP. The power management circuit includes DC-DC converter and feed forward maximum power point tracking algorithm to transfer maximum power from the single solar cell. The system has ultra-low power battery protection and input condition sensor circuit to extend the life of the battery by protecting from overcharging and over discharging. Also, cold start up circuit is used to run the system when battery voltage drains out to zero. The objective of this system to make complete energy harvester unit is to drive wide range of ultra-low power applications. We have driven the ZigBee receiver to validate our system and the system works effectively

An Inductor-Less Multiple Input Single Output (MISO) Energy Harvester Achieving 74.6% Efficiency with Simultaneous MPPT

This work presents an inductor less switched capacitor based energy harvester, which can simultaneously harvest from 2 energy sources (Solar + Piezo). The proposed harvester employs 2D maximum power point tracking algorithm, by changing the conversion ratios of the charge pumps for piezo and solar sources, and 1D voltage regulation algorithm through varying the switching frequency. The proposed 2D MPPT can match the input impedance of two sources simultaneously. Implemented in 65nm CMOS, the proposed harvester can generate 1.8-2.5V output while delivering 35uW to 70uW power with a peak efficiency of 74.6%

ISM-Band Energy Harvesting Wireless Sensor Node

In recent years, the interest in remote wireless sensor networks has grown significantly, particularly with the rapid advancements in Internet of Things (IoT) technology. These networks find diverse applications, from inventory tracking to environmental monitoring. In remote areas where grid access is unavailable, wireless sensors are commonly powered by batteries, which imposes a constraint on their lifespan. However, with the emergence of wireless energy harvesting technologies, there is a transformative potential in addressing the power challenges faced by these sensors. By harnessing energy from the surrounding environment, such as solar, thermal, vibrational, or RF sources, these sensors can potentially operate autonomously for extended periods. This innovation not only enhances the sustainability of wireless sensor networks but also paves the way for a more energy-efficient and environmentally conscious approach to data collection and monitoring in various applications. This work explores the development of an RF-powered wireless sensor node in 22nm FDSOI technology working in the ISM band for energy harvesting and wireless data transmission. The sensor node encompasses power-efficient circuits, including an RF energy harvesting module equipped with a multi-stage RF Dickson rectifier, a robust power management unit, a DLL and XOR-based frequency synthesizer for RF carrier generation, and a class E power amplifier. To ensure the reliability of the WSN, a dedicated wireless RF source powers up the WSN. Additionally, the RF signal from this dedicated source serves as the reference frequency input signal for synthesizing the RF carrier for wireless data transmission, eliminating the need for an on-chip local oscillator. This approach achieves high integration and proves to be a cost-effective implementation of efficient wireless sensor nodes. The receiver and energy harvester operate at 915 MHz Frequency, while the transmitter functions at 2.45 GHz, employing On-Off Keying (OOK) for data modulation. The WSN utilizes an efficient RF rectifier design featuring a remarkable power conversion efficiency, reaching 55% at an input power of -14 dBm. Thus, the sensor node can operate effectively even with an extremely low RF input power of -25 dBm. The work demonstrates the integration of the wireless sensor node with an ultra-low-power temperature sensor, designed using 65 nm CMOS technology. This temperature sensor features an ultra-low power consumption of 60 nW and a Figure of Merit (FOM) of 0.022 [nJ.K-2]. The WSN demonstrated 55% power efficiency at a TX output power of -3.8 dBm utilizing a class E power amplifier

Efficient Archietecture for Effective Utilization of Harvested Power in Microscale Energy Harvesting

Recent developments in combining sensors, microprocessors, and radio frequency (RF) communications holds the potential to revolutionize the way we monitor and maintain critical systems. In the future, literally billions of wireless sensors may become deeply embedded within machines, structures, and the environment. Sensed information will be automatically collected, compressed, and forwarded for condition based maintenance. Energy Harvesting comprises a promising solution to one of the key problems faced by battery-powered Wireless Sensor Networks, namely the limited nature of the energy supply (finite battery capacity). By harvesting energy from the surrounding environment, the sensors can have a continuous lifetime without any needs for battery recharge or replacement

Circuits and Systems for Energy Harvesting and Internet of Things Applications

The Internet of Things (IoT) continues its growing trend, while new “smart” objects are con-stantly being developed and commercialized in the market. Under this paradigm, every common object will be soon connected to the Internet: mobile and wearable devices, electric appliances, home electronics and even cars will have Internet connectivity. Not only that, but a variety of wireless sensors are being proposed for different consumer and industrial applications. With the possibility of having hundreds of billions of IoT objects deployed all around us in the coming years, the social implications and the economic impact of IoT technology needs to be seriously considered. There are still many challenges, however, awaiting a solution in order to realize this future vision of a connected world. A very important bottleneck is the limited lifetime of battery powered wireless devices. Fully depleted batteries need to be replaced, which in perspective would generate costly maintenance requirements and environmental pollution. However, a very plausible solution to this dilemma can be found in harvesting energy from the ambient. This dissertation focuses in the design of circuits and system for energy harvesting and Internet of Things applications. The first part of this dissertation introduces the research motivation and fundamentals of energy harvesting and power management units (PMUs). The architecture of IoT sensor nodes and PMUs is examined to observe the limitations of modern energy harvesting systems. Moreover, several architectures for multisource harvesting are reviewed, providing a background for the research presented here. Then, a new fully integrated system architecture for multisource energy harvesting is presented. The design methodology, implementation, trade-offs and measurement results of the proposed system are described. The second part of this dissertation focus on the design and implementation of low-power wireless sensor nodes for precision agriculture. First, a sensor node incorporating solar energy harvesting and a dynamic power management strategy is presented. The operation of a wireless sensor network for soil parameter estimation, consisting of four nodes is demonstrated. After that, a solar thermoelectric generator (STEG) prototype for powering a wireless sensor node is proposed. The implemented solar thermoelectric generator demonstrates to be an alternative way to harvest ambient energy, opening the possibility for its use in agricultural and environmental applications. The open problems in energy harvesting for IoT devices are discussed at the end, to delineate the possible future work to improve the performance of EH systems. For all the presented works, proof-of-concept prototypes were fabricated and tested. The measured results are used to verify their correct operation and performance

On-Chip Solar Energy Harvester and PMU With Cold Start-Up and Regulated Output Voltage for Biomedical Applications

This paper presents experimental results from a system that comprises a fully autonomous energy harvester with a solar cell of 1 mm 2 as energy transducer and a Power Management Unit (PMU) on the same silicon substrate, and an output voltage regulator. Both chips are implemented in standard 0.18 μm CMOS technology with total layout areas of 1.575 mm 2 and 0.0126 mm 2 , respectively. The system also contains an off-the-shelf 3.2 mm × 2.5 mm × 0.9 mm supercapacitor working as an off-chip battery or energy reservoir between the PMU and the voltage regulator. Experimental results show that the fast energy recovery of the on-chip solar cell and PMU permits the system to replenish the supercapacitor with enough charge as to sustain Bluetooth Low Energy (BLE) communications even with input light powers of 510 nW. The whole system is able to self-start-up without external mechanisms at 340 nW. This work is the first step towards a self-supplied sensor node with processing and communication capabilities. The small form factor and ultra-low power consumption of the system components is in compliance with biomedical applications requirementsThis work was supported in part by the Spanish Government (Ministerio de Ciencia, Innovación y Universidades) under Project RTI2018-097088-B-C32 and Project RTI2018-095994-B-I00 (MICINN/FEDER), in part by the Xunta de Galicia, in part by the Consellería de Cultura, Educación e Ordenación Universitaria (accreditation 2016-2019, ED431G/08 and reference competitive group 2017-2020, ED431C 2017/69) and European Regional Development Fund (ERDF), and in part by the Junta de Extremadura and the ERDF, under Grant IB 18079S