Energy Harvesting Triboelectric Nano-Generators for the Internet-of-Things

Lead Research Organisation: University of Surrey
Department Name: ATI Electronics


Next generation technologies, such as the IoT and 5G technology, are shaping to enhance the standard of life of people by creating a digitally connected world, in which the productivity, health, and communication will be vastly improved. This involves integrating sensors, intelligent circuits and miniature electronic devices into day to day objects around us, including the human body, clothing, buildings, vehicles and streets etc. Such systems become increasingly feasible due to the advancements in low-power electronics and IoT technologies, however, powering these electronics with the required complexity, flexibility, mobility and self-powered capabilities remains one of the key challenges in the modern era. Scavenging power from freely available ambient mechanical energy sources, such as human motion, wind, wave energy and machine vibrations, has been proven to be a viable approach to fulfil such energy and performance requirements.

The triboelectric Nanogenerator (TENG) is one of the leading candidates to emerge as a potential energy source for powering autonomous IoT applications. These devices have shown the capability of capturing waste mechanical energy from ambient sources and easily producing a few Watts of output power, with high conversion efficiencies reported. However, knowledge of the electromagnetic behaviour of TENGs and the exact way they operate has been lacking in the past. Consequently, the relationship between the structural, material and motion parameters with the output power has not been adequately studied. This has resulted in non-optimised TENG architectures which suffer from relatively low, instantaneous and irregular output power, along with an impedance mismatch between the TENG and the output applications. Such issues decrease the output power of the TENG and significantly reduce its efficiency. This in turn associates with numerous other issues such as elevated cost, higher carbon footprint, larger device size and unreliable power supply.

Recently, we introduced the distance-dependent electric field (DDEF) model, the first analytical theoretical model to fully describe the working principles of TENGs, using Maxwell's equations. This model has been proven to accurately predict the output behaviour of different TENG working modes and has been successfully applied to develop optimisation strategies for simple planar TENGs, significantly reducing most issues described above.

In the proposed project, we will use the DDEF model to optimise material, device and motion parameters of TENGs to develop autonomous energy harvesters for IoT applications such as health sensors, wireless communication networks, portable and wearable electronics. We will first assess the energy requirements of IoT devices and design TENGs with suitable efficiencies to capture that energy from ambient sources. These devices are then finetuned to obtain the ideal size, shape, and material type, which will fit the applications while providing optimum electric field distribution, resulting in increased power outputs. We will use commonly available, low cost and flexible triboelectric polymers (eg: nylon, PET) as TENG layers, and further use scalable low-cost manufacturing techniques. Nanotechnology based surface improvements will be conducted to further improve the efficiency of these devices. The suggested improvements will increase the output power by about 100% compared to a non-optimised device, as evident from our simulation and calculation results. To ensure a non-interrupted regular power supply, we will integrate many TENG units with calculated phase differences, which would result in a near DC output current. Finally, we will combine the power management circuits and energy storage units (eg: supercapacitors and flexible batteries) along with the TENG to the IoT module, to assemble the fully integrated self-powered IoT devices.

Planned Impact

The objectives of this project are to develop broad theoretical understanding of the working principles of TENGs and to implement this knowledge to develop optimised energy harvesters, which can capture ambient mechanical movement to power IoT devices. We are attempting to design and develop second generation TENG architectures, by boosting the output power through strategic optimisation of material, structural and motion parameters. This technology will encompass number of different scenarios of energy harvesting for IoT applications, for instance, exploitation of human motion, wind, waves and vibration of vehicles to power health sensors, communication devices, and personal electronics. The potential of such a technology in powering IoT, 5G and Big Data applications which require high degree of mobility and autonomous operation, is obvious. However, with the increase in efficiency and effective power management envisaged, larger scale power scavenging scenarios can be proposed with ultimately distributed smart grid type applications.

The economy will benefit from the supply chain development to produce TENG technology, its deployment and management. IoT and flexible electronics will contain their own power supply, allowing better design and construction of electronic devices. Furthermore, smart applications that can operate in the small to medium scale energy production arena with remote powering will be enabled. Such technologies would have an immense impact on the development of remote areas in third world countries by disseminating information and energy. Furthermore, this technology will open the pathways to exploit the energy harvesting market, which is predicted to reach £ 2.6 billion by the year 2020. Most importantly, TENG technology will make use of otherwise wasted energy and enable its contribution towards the energy economy.

The programme we develop will have the technology push strand as well as the industry pull strand covered by having a two-way dialogue very early on with all stakeholders. We hope to organise our own information meeting in year 2/3, and also work closely with the NPL and the other industrial partners to take part in information dissemination and scoping work programmes. We have also discussed the possibility of a scoping programme within the university (ATI, 5GIC) and with the collaborating institutes such as NPL and Georgia Tech, in Large Area Electronics.

In the shorter term, several outcomes may have potential commercial impact (eg. IP protection), and exploitation will be managed in with the advice and aid of the Research and Enterprise Support (RES) office of the University. The RES division provides the academic team with the necessary management, bid co-ordination and IP exploitation skills and assistance. The Technology Transfer Office (TTO) within RES is responsible for the protection and exploitation of intellectual property developed by staff and has already acted upon numerous developments by researchers in the ATI. The University of Surrey has a strong track record for commercial exploitation of research, with many successful spinout companies.
Description A number of research papers including theoretical modelling of the triboelectric generator process has been published.

We also were featured in a BBC technology news release in 2020.

We continue to progress building wearable and sustainable energy harvesting devices that can be used for autonomous activities.
Exploitation Route We are building demonstrators based on this technology at present to increase the TRL.
Sectors Electronics,Energy,Transport

Description QinetiQ partnership on energy materials 
Organisation Qinetiq
Department QinetiQ (Farnborough)
Country United Kingdom 
Sector Private 
PI Contribution We have now set up a joint laboratories between QinetiQ and Surrey on sharing capability in energy materials and in particular on wearable technologies.
Collaborator Contribution QinetiQ have provided invaluable support, advisory board membership and mentoring, and started an iCASE award in Oct. 2019 valued at £88k to work on this project.
Impact Joint research and laboratory capability made available in 2020.
Start Year 2017