Real World Assessment of an Auto-parametric Electromagnetic Vibration Energy Harvester

The convention within the eld of vibration energy harvesting (VEH) has revolved around designing resonators with natural frequencies that match single fixed frequency sinusoidal input. However, real world vibrations can be random, multi-frequency, broadband and time-varying in nature. Building upon previous work on auto-parametric resonance, the fundamentally different approach allows multiple axes vibration and has the potential to achieve higher power density as well as wider operational frequency bandwidth. This paper presents the power response of a packaged auto-parametric VEH prototype (practical operational volume 126 cm^3) towards various real world vibration sources including vibration of a bridge, a compressor motor as well as an automobile. At auto-parametric resonance (driven at 23.5 Hz and 1 grms), the prototype can output a peak of 78.9 mW and 4.5 Hz of -3dB bandwidth. Furthermore, up to ~1 mW of average power output was observed from the harvester on the Forth Road Bridge. The harvested electrical energy from various real world sources were used to power up a power conditioning circuit, a wireless sensor mote, a MEMS (micro-electromechanical system) accelerometer and other low power sensors. This demonstrates the concept of self-sustaining vibration-powered wireless sensor systems in real world scenarios, to potentially realise maintenance-free autonomous structural health and condition monitoring.This work was supported by EPSRC (grant EP/L010917/1) and the Cambridge Centre for Smart Infrastructure and Construction

A Hybrid Vibration Powered Microelectromechanical Strain Gauge

This paper reports the demonstration of an ultra-low power MEMS-CMOS oscillator for strain sensing, powered by a miniature piezoelectric vibration energy harvester (VEH). The employment of the Pierce oscillator topology in a MEMS-CMOS oscillator allows for minimisation of the power requirement to as low as 1.1 µW under ideal conditions. A VEH prototype, developed with hard PZT on a stainless steel substrate (∼0.4 cm3 practical operational volume), is able to deliver a typical average power of 187 µW at 11.4 ms−2 and 514 Hz. Some of the practical challenges associated with the integration of the harvester and the MEMS sensor have also been explored, which helps to lay the foundation for realising net-zero-power strain sensors.This work was supported by EPSRC (grants: EP/K000314/1 and EP/L010917/1).This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/JSEN.2015.247929

Online Condition Monitoring of Rotating Machines by Self-Powered Piezoelectric Transducer from Real-Time Experimental Investigations

This paper investigates self-powering online condition monitoring for rotating machines by the piezoelectric transducer as an energy harvester and sensor. The method is devised for real-time working motors and relies on self-powered wireless data transfer where the data comes from the piezoelectric transducer’s output. Energy harvesting by Piezoceramic is studied under real-time motor excitations, followed by power optimization schemes. The maximum power and root mean square power generation from the motor excitation are 13.43 mW/g(2) and 5.9 mW/g(2), which can be enough for providing autonomous wireless data transfer. The piezoelectric transducer sensitivity to the fault is experimentally investigated, showing the considerable fault sensitivity of piezoelectric transducer output to the fault. For instance, the piezoelectric transducer output under a shaft-misalignment fault is more than 200% higher than the healthy working conditions. This outcome indicates that the monitoring of rotating machines can be achieved by using a self-powered system of the piezoelectric harvesters. Finally, a discussion on the feasible self-powered online condition monitoring is presented

Energy harvesting towards self-powered iot devices

The internet of things (IoT) manages a large infrastructure of web-enabled smart devices, small devices that use embedded systems, such as processors, sensors, and communication hardware to collect, send, and elaborate on data acquired from their environment. Thus, from a practical point of view, such devices are composed of power-efficient storage, scalable, and lightweight nodes needing power and batteries to operate. From the above reason, it appears clear that energy harvesting plays an important role in increasing the efficiency and lifetime of IoT devices. Moreover, from acquiring energy by the surrounding operational environment, energy harvesting is important to make the IoT device network more sustainable from the environmental point of view. Different state-of-the-art energy harvesters based on mechanical, aeroelastic, wind, solar, radiofrequency, and pyroelectric mechanisms are discussed in this review article. To reduce the power consumption of the batteries, a vital role is played by power management integrated circuits (PMICs), which help to enhance the system's life span. Moreover, PMICs from different manufacturers that provide power management to IoT devices have been discussed in this paper. Furthermore, the energy harvesting networks can expose themselves to prominent security issues putting the secrecy of the system to risk. These possible attacks are also discussed in this review article

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

Power Processing for Electrostatic Microgenerators

Microgenerators are electro-mechanical devices which harvest energy from local environmental from such sources as light, heat and vibrations. These devices are used to extend the life-time of wireless sensor network nodes. Vibration-based microgenerators for biomedical applications are investigated in this thesis. In order to optimise the microgenerator system design, a combined electro-mechanical system simulation model of the complete system is required. In this work, a simulation toolkit (known as ICES) has been developed utilising SPICE. The objective is to accurately model end-to-end microgenerator systems. Case-study simulations of electromagnetic and electrostatic microgenerator systems are presented to verify the operation of the toolkit models. Custom semiconductor devices, previously designed for microgenerator use, have also been modelled so that system design and optimisation of complete microgenerator can be accomplished. An analytical framework has been developed to estimate the maximum system effectiveness of an electrostatic microgenerator operating in constant-charge and constant-voltage modes. The calculated system effectiveness values are plotted with respect to microgenerator sizes for different input excitations. Trends in effectiveness are identified and discussed in detail. It was found that when the electrostatic transducer is interfaced with power processing circuit, the parasitic elements of the circuit are reducing the energy generation ability of the transducer by sharing the charge during separation of the capacitor plates. Also, found that in constant-voltage mode the electrostatic microgenerator has a better effectiveness over a large operating range than constant-charge devices. The ICES toolkit was used to perform time-domain simulation of a range of operating points and the simulation results provide verification of the analytical results

Wireless Condition Monitoring System for Rotating Machinery Powered by a Hybrid Vibration Based Energy Harvester / Mohd Sofwan Mohd Resali and Hanim Salleh

This paper presents the development of wireless condition monitoring system for rotating machinery powered by a hybrid vibration based energy harvester. The self-powered condition monitoring system consists of three parts. The first part of the system is the energy harvester, the second part is the power management and the third part is the android based user interface. The system used a hybrid energy harvester (piezoelectric and electromagnetic) to harvest energy from the vibrating machine at a resonance frequency of 50±2 Hz and 0.25g ms-2 of acceleration. The maximum output power from the hybrid harvester was 3.00 mW at 200 kΩ of load resistor. The power management circuit efficiency was 85% with output power of 2.55 mW. An accelerometer sensor and a temperature sensor were connected to the power management unit to sense the vibration and temperature level of the machine. Data from the sensors were transmitted through the wireless Bluetooth dongle to the android phone for end user monitoring. An android application was developed to receive the acceleration and temperature condition monitoring. At maximum power, initial charging duration of the supercapacitor was 130 seconds, and duration for recharging to 8.2V was 15 seconds. Therefore, the self-powered system managed to transmit data to the android application 15 second’s intervals

Low power CMOS IC, biosensor and wireless power transfer techniques for wireless sensor network application

The emerging field of wireless sensor network (WSN) is receiving great attention due to the interest in healthcare. Traditional battery-powered devices suffer from large size, weight and secondary replacement surgery after the battery life-time which is often not desired, especially for an implantable application. Thus an energy harvesting method needs to be investigated. In addition to energy harvesting, the sensor network needs to be low power to extend the wireless power transfer distance and meet the regulation on RF power exposed to human tissue (specific absorption ratio). Also, miniature sensor integration is another challenge since most of the commercial sensors have rigid form or have a bulky size. The objective of this thesis is to provide solutions to the aforementioned challenges

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