Piezoelectric vibration energy harvesting from airflow in HVAC (Heating Ventilation and Air Conditioning) systems

This study focuses on the design and wind tunnel testing of a high efficiency Energy Harvesting device, based on piezoelectric materials, with possible applications for the sustainability of smart buildings, structures and infrastructures. The development of the device was supported by ESA (the European Space Agency) under a program for the space technology transfer in the period 2014-2016. The EH device harvests the airflow inside Heating, Ventilation and Air Conditioning (HVAC) systems, using a piezoelectric component and an appropriate customizable aerodynamic appendix or fin that takes advantage of specific airflow phenomena (vortex shedding and galloping), and can be implemented for optimizing the energy consumption inside buildings. Focus is given on several relevant aspects of wind tunnel testing: different configurations for the piezoelectric bender (rectangular, cylindrical and T-shaped) are tested and compared, and the effective energy harvesting potential of a working prototype device is assessed

Energy Harvesting and Management for Wireless Autonomous Sensors

Wireless autonomous sensors that harvest ambient energy are attractive solutions, due to their convenience and economic benefits. A number of wireless autonomous sensor platforms which consume less than 100?W under duty-cycled operation are available. Energy harvesting technology (including photovoltaics, vibration harvesters, and thermoelectrics) can be used to power autonomous sensors. A developed system is presented that uses a photovoltaic module to efficiently charge a supercapacitor, which in turn provides energy to a microcontroller-based autonomous sensing platform. The embedded software on the node is structured around a framework in which equal precedent is given to each aspect of the sensor node through the inclusion of distinct software stacks for energy management and sensor processing. This promotes structured and modular design, allowing for efficient code reuse and encourages the standardisation of interchangeable protocols

Performance testing of a low power consumption wireless sensor communication system integrated with an energy harvesting power source

This paper presents the performance testing results of a wireless sensor communication system with low power consumption integrated with a vibration energy harvesting power source. The experiments focus on the system’s capability to perform continuous monitoring and to wirelessly transmit the data acquired from the sensors to a user base station, completely battery-free. Energy harvesting technologies together with system design optimisation for power consumption minimisation ensure the system’s energy autonomous capability demonstrated in this paper by presenting the promising testing results achieved following its integration with Structural Health Monitoring (SHM) and Body Area Network (BAN) applications

Wireless sensor networks with energy harvesting: Modeling and simulation based on a practical architecture using real radiation levels

This paper presents a new energy-harvesting model for a network simulator that implements super-capacitor energy storage with solar energy-harvesting recharge. The model is easily extensible, and other energyharvesting systems, or different energy storages, can be further developed. Moreover, code can be conveniently reused as the implementation is entirely uncoupled from the radio and node models. Real radiation data are obtained from available online databases in order to dynamically calculate super-capacitor charge and discharge. Such novelty enables the evaluation of energy evolution on a network of sensor nodes at various physical world locations and during different seasons. The model is validated against a real and fully working prototype, and good result correlation is shown. Furthermore, various experiments using the ns-3 simulator were conducted, demonstrating the utility of the model in assisting the research and development of the deployment of everlasting wireless sensor networks.This work was supported by the CICYT (research projects CTM2011-29691-C02-01 and TIN2011-28435-C03-01) and UPV research project SP20120889.Climent, S.; Sánchez Matías, AM.; Blanc Clavero, S.; Capella Hernández, JV.; Ors Carot, R. (2013). Wireless sensor networks with energy harvesting: Modeling and simulation based on a practical architecture using real radiation levels. Concurrency and Computation: Practice and Experience. 1-19. https://doi.org/10.1002/cpe.3151S119Akyildiz, I. F., & Vuran, M. C. (2010). Wireless Sensor Networks. doi:10.1002/9780470515181Seah, W. K. G., Tan, Y. K., & Chan, A. T. S. (2012). Research in Energy Harvesting Wireless Sensor Networks and the Challenges Ahead. Autonomous Sensor Networks, 73-93. doi:10.1007/5346_2012_27Vullers, R., Schaijk, R., Visser, H., Penders, J., & Hoof, C. (2010). Energy Harvesting for Autonomous Wireless Sensor Networks. IEEE Solid-State Circuits Magazine, 2(2), 29-38. doi:10.1109/mssc.2010.936667Ammar, Y., Buhrig, A., Marzencki, M., Charlot, B., Basrour, S., Matou, K., & Renaudin, M. (2005). Wireless sensor network node with asynchronous architecture and vibration harvesting micro power generator. Proceedings of the 2005 joint conference on Smart objects and ambient intelligence innovative context-aware services: usages and technologies - sOc-EUSAI ’05. doi:10.1145/1107548.1107618Vijayaraghavan, K., & Rajamani, R. (2007). Active Control Based Energy Harvesting for Battery-Less Wireless Traffic Sensors. 2007 American Control Conference. doi:10.1109/acc.2007.4282842Bottner, H., Nurnus, J., Gavrikov, A., Kuhner, G., Jagle, M., Kunzel, C., … Schlereth, K.-H. (2004). New thermoelectric components using microsystem technologies. Journal of Microelectromechanical Systems, 13(3), 414-420. doi:10.1109/jmems.2004.828740Mateu L Codrea C Lucas N Pollak M Spies P Energy harvesting for wireless communication systems using thermogenerators Conference on Design of Circuits and Integrated Systems (DCIS) 2006AEMet Agencia Estatal de Meteorolgía 2013 http//www.aemet.esPANGAEA Data Publisher for Earth & Environmental Science 2013 http://www.pangaea.de/Zeng, K., Ren, K., Lou, W., & Moran, P. J. (2007). Energy aware efficient geographic routing in lossy wireless sensor networks with environmental energy supply. Wireless Networks, 15(1), 39-51. doi:10.1007/s11276-007-0022-0Hasenfratz, D., Meier, A., Moser, C., Chen, J.-J., & Thiele, L. (2010). Analysis, Comparison, and Optimization of Routing Protocols for Energy Harvesting Wireless Sensor Networks. 2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing. doi:10.1109/sutc.2010.35Noh, D. K., & Hur, J. (2012). Using a dynamic backbone for efficient data delivery in solar-powered WSNs. Journal of Network and Computer Applications, 35(4), 1277-1284. doi:10.1016/j.jnca.2012.01.012Lin, L., Shroff, N. B., & Srikant, R. (2007). Asymptotically Optimal Energy-Aware Routing for Multihop Wireless Networks With Renewable Energy Sources. IEEE/ACM Transactions on Networking, 15(5), 1021-1034. doi:10.1109/tnet.2007.896173Ferry, N., Ducloyer, S., Julien, N., & Jutel, D. (2011). Power/Energy Estimator for Designing WSN Nodes with Ambient Energy Harvesting Feature. EURASIP Journal on Embedded Systems, 2011(1), 242386. doi:10.1155/2011/242386Glaser, J., Weber, D., Madani, S., & Mahlknecht, S. (2008). Power Aware Simulation Framework for Wireless Sensor Networks and Nodes. EURASIP Journal on Embedded Systems, 2008(1), 369178. doi:10.1155/2008/369178De Mil, P., Jooris, B., Tytgat, L., Catteeuw, R., Moerman, I., Demeester, P., & Kamerman, A. (2010). Design and Implementation of a Generic Energy-Harvesting Framework Applied to the Evaluation of a Large-Scale Electronic Shelf-Labeling Wireless Sensor Network. EURASIP Journal on Wireless Communications and Networking, 2010(1). doi:10.1155/2010/343690Castagnetti, A., Pegatoquet, A., Belleudy, C., & Auguin, M. (2012). A framework for modeling and simulating energy harvesting WSN nodes with efficient power management policies. EURASIP Journal on Embedded Systems, 2012(1). doi:10.1186/1687-3963-2012-8Alippi, C., & Galperti, C. (2008). An Adaptive System for Optimal Solar Energy Harvesting in Wireless Sensor Network Nodes. IEEE Transactions on Circuits and Systems I: Regular Papers, 55(6), 1742-1750. doi:10.1109/tcsi.2008.922023Xiaofan Jiang, Polastre, J., & Culler, D. (s. f.). Perpetual environmentally powered sensor networks. IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005. doi:10.1109/ipsn.2005.1440974Simjee, F., & Chou, P. H. (2006). Everlast. Proceedings of the 2006 international symposium on Low power electronics and design - ISLPED ’06. doi:10.1145/1165573.1165619Sánchez, A., Climent, S., Blanc, S., Capella, J. V., & Piqueras, I. (2011). WSN with energy-harvesting. Proceedings of the 6th ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks - PM2HW2N ’11. doi:10.1145/2069087.2069091Renner C Jessen J Turau V Lifetime prediction for supercapacitor-powered wireless sensor nodes Proc. of the 8th GI/ITG KuVS Fachgesprächİ Drahtlose Sensornetze(FGSN09) 2009TI Analog, Embedded Processing, Semiconductor Company, Texas Instruments 2013 http//www.ti.comWSNVAL Wireless Sensor Networks Valencia 2013 www.wsnval.comSanchez, A., Blanc, S., Yuste, P., & Serrano, J. J. (2011). RFID Based Acoustic Wake-Up System for Underwater Sensor Networks. 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems. doi:10.1109/mass.2011.103Fan, K.-W., Zheng, Z., & Sinha, P. (2008). Steady and fair rate allocation for rechargeable sensors in perpetual sensor networks. Proceedings of the 6th ACM conference on Embedded network sensor systems - SenSys ’08. doi:10.1145/1460412.1460436Moser, C., Thiele, L., Brunelli, D., & Benini, L. (2010). Adaptive Power Management for Environmentally Powered Systems. IEEE Transactions on Computers, 59(4), 478-491. doi:10.1109/tc.2009.15

Photovoltaic sample-and-hold circuit enabling MPPT indoors for low-power systems

Photovoltaic (PV) energy harvesting is commonly used to power autonomous devices, and maximum power point tracking (MPPT) is often used to optimize its efficiency. This paper describes an ultra low-power MPPT circuit with a novel sample-and-hold and cold-start arrangement, enabling MPPT across the range of light intensities found indoors, which has not been reported before. The circuit has been validated in practice and found to cold-start and operate from 100 lux (typical of dim indoor lighting) up to 5000 lux with a 55cm2 amorphous silicon PV module. It is more efficient than non-MPPT circuits, which are the state-of-the-art for indoor PV systems. The proposed circuit maximizes the active time of the PV module by carrying out samples only once per minute. The MPPT control arrangement draws a quiescent current draw of only 8uA, and does not require an additional light sensor as has been required by previously-reported low-power MPPT circuits

A Survey of Multi-Source Energy Harvesting Systems

Energy harvesting allows low-power embedded devices to be powered from naturally-ocurring or unwanted environmental energy (e.g. light, vibration, or temperature difference). While a number of systems incorporating energy harvesters are now available commercially, they are specific to certain types of energy source. Energy availability can be a temporal as well as spatial effect. To address this issue, ‘hybrid’ energy harvesting systems combine multiple harvesters on the same platform, but the design of these systems is not straightforward. This paper surveys their design, including trade-offs affecting their efficiency, applicability, and ease of deployment. This survey, and the taxonomy of multi-source energy harvesting systems that it presents, will be of benefit to designers of future systems. Furthermore, we identify and comment upon the current and future research directions in this field

Flexible Integration of Alternative Energy Sources for Autonomous Sensing

Recent developments in energy harvesting and autonomous sensing mean that it is now possible to power sensors solely from energy harvested from the environment. Clearly this is dependent on sufficient environmental energy being present. The range of feasible environments for operation can be extended by combining multiple energy sources on a sensor node. The effective monitoring of their energy resources is also important to deliver sustained and effective operation. This paper outlines the issues concerned with combining and managing multiple energy sources on sensor nodes. This problem is approached from both a hardware and embedded software viewpoint. A complete system is described in which energy is harvested from both light and vibration, stored in a common energy store, and interrogated and managed by the node

Towards energy-autonomous wake-up receiver using visible light communication

The use of Visible Light Communication (VLC) in wake-up communication systems is a potential energy-efficient and low-cost solution for wireless communication of consumer electronics. In this paper, we go one step further and propose the use of visible light both for wake-up communication and energy harvesting purposes, with the final objective of an energy-autonomous wake-up receiver module. We first present the details and the design criteria of this novel system. We then present the results of evaluation of design criteria such as solar panel and capacitor type choices. To evaluate the performance of the developed wake-up system with energy-autonomous receiver system, we perform realistic indoor scenario tests, analyzing the effect of varying distances, angles, and light intensities as well as the effect of presence of interfering lights.Peer ReviewedPostprint (author's final draft

Radio frequency energy harvesting for autonomous systems

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyRadio Frequency Energy Harvesting (RFEH) is a technology which enables wireless power delivery to multiple devices from a single energy source. The main components of this technology are the antenna and the rectifying circuitry that converts the RF signal into DC power. The devices which are using Radio Frequency (RF) power may be integrated into Wireless Sensor Networks (WSN), Radio Frequency Identification (RFID), biomedical implants, Internet of Things (IoT), Unmanned Aerial Vehicles (UAVs), smart meters, telemetry systems and may even be used to charge mobile phones. Aside from autonomous systems such as WSNs and RFID, the multi-billion portable electronics market – from GSM phones to MP3 players – would be an attractive application for RF energy harvesting if the power requirements are met. To investigate the potential for ambient RFEH, several RF site surveys were conducted around London. Using the results from these surveys, various harvesters were designed and tested for different frequency bands from the RF sources with the highest power density within the Medium Wave (MW), ultra- and super-high (UHF and SHF) frequency spectrum. Prototypes were fabricated and tested for each of the bands and proved that a large urban area around Brookmans park radio centre is suitable location for harvesting ambient RF energy. Although the RFEH offers very good efficiency performance, if a single antenna is considered, the maximum power delivered is generally not enough to power all the elements of an autonomous system. In this thesis we present techniques for optimising the power efficiency of the RFEH device under demanding conditions such as ultra-low power densities, arbitrary polarisation and diverse load impedances. Subsequently, an energy harvesting ferrite rod rectenna is designed to power up a wireless sensor and its transmitter, generating dedicated Medium Wave (MW) signals in an indoor environment. Harvested power management, application scenarios and practical results are also presented