Self-Powered Sensing via Energy Harvesting, enabling Wireless Sensor Networks and the Internet of Things
Our research focuses on developing energy harvesting concepts for self-powered sensing using fundamentals of dynamics and nonlinear vibrations.
Wireless sensor networks are used for real-time structural, environmental and human health monitoring, empowering the Internet of Things.
The benefits can be enormous, ranging from detecting faults in expensive infrastructure (e.g. wind turbines), reducing maintenance costs, and collecting information from ecosystems up to improving healthcare, emergency responses and entertainment using wearable sensors.
A key challenge in deploying wireless sensor networks is their power supply: batteries have limited lifespan, whereas harnessing power supply can be impractical for applications involving motion and remote or non-accessible locations.
Our Aim
Our research focuses on developing energy harvesting concepts for self-powered sensing using fundamentals of dynamics and nonlinear vibrations.
Our energy harvesters can collect ambient energy in a broadband manner e.g. from wind, vibration, fluid flow, using various transduction mechanisms to power either off-the-shelf or bespoke sensors.
Power management and wireless data communication complete the loop, integrated with the harvester. Thus, self-powered sensing is achieved, eliminating batteries and the data collected by the sensor are transmitted wirelessly.
Our research
We employ fundamental attributes of linear and nonlinear dynamics to design miniaturised, bespoke energy harvesters based on frequency tunability, broadband aggressive oscillations and stability characteristics.
Our research is transformed into design reality, targeting different applications, such as propulsion systems, environmental monitoring, and infrastructure assets. We develop translational and rotational bespoke energy harvesting concepts according to the operating conditions of the host system, the power requirements and miniaturisation attributes.
Research outcome
We have modelled, developed and patented energy harvesting concepts that can generate sufficient amounts of power (up to tens of mW rms) for autonomous power sensing. The robustness of their operation under a variety of operating conditions have been demonstrated as proof of concepts in the laboratory.
Our research has been funded by the Engineering and Physical Sciences Research Council (EP/L019426/1, Targeted energy transfer in powertrains to reduce vibration-induced energy losses), the Enterprise Projects Group (miniaturisation of vibration energy harvester device for powering sensors in propulsion applications) and Game Changers (in collaboration with the National Nuclear Laboratory).
Research dissemination
Our research has been promoted and disseminated at International Conferences, such as IEEE PowerMEMS, ASME IDETC, ENOC and via social media channels.
Research members
Selected publications
- Masabi, SN, Fu, H, Flint, J, Theodossiades, S (2024) , Smart Materials and Structures, ISSN: 0964-1726. DOI: 10.1088/1361-665x/ad649b.
- Masabi, S, Fu, H, Flint, J, Theodossiades, S (2024) , Applied Energy, 365(2024), 123200, ISSN: 0306-2619. DOI: 10.1016/j.apenergy.2024.123200.
- Masabi, S, Fu, H, Theodossiades, S (2022) , Journal of Physics D: Applied Physics, 56(2), 024001, ISSN: 0022-3727. DOI: 10.1088/1361-6463/aca4de.
- Gunn, BE, Alevras, P, Flint, J, Fu, H, Rothberg, S, Theodossiades, S (2021) , Applied Energy, 302, 117479, ISSN: 0306-2619. DOI: 10.1016/j.apenergy.2021.117479.
- Gunn, B, Theodossiades, S, Rothberg, S (2021) , Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 235(21), pp.5275-5287, ISSN: 0954-4062. DOI: 10.1177/0954406220985199.
- Fu, H, Theodossiades, S, Gunn, B, Abdallah, I, Chatzi, E (2020) , Nonlinear Dynamics, 101(4), pp.2131-2143, ISSN: 0924-090X. DOI: 10.1007/s11071-020-05889-9.
- Gunn, B, Theodossiades, S, Rothberg, S (2019) , Journal of Vibration and Acoustics, 141(3), 031005, ISSN: 1048-9002. DOI: 10.1115/1.4042040.
- Alevras, P and Theodossiades, S (2018) , Journal of Sound and Vibration, ISSN: 0022-460X. DOI: 10.1016/j.jsv.2018.11.007.
- Alevras, P, Theodossiades, S, Rahnejat, H (2018) , Nonlinear Dynamics, 92, pp.1271-1286, ISSN: 0924-090X. DOI: 10.1007/s11071-018-4124-2.