| KEYWORD |
Innovative solutions for energy harvesting, theory and modelling
keywords CIRCUIT THEORY, ENERGY HARVESTING, NONLINEAR DYNAMICS, STOCHASTIC PROCESSES
Reference persons FABRIZIO BONANI, MICHELE BONNIN
External reference persons Fabio Lorenzo Traversa
Research Groups Linear and Nonlinear Circuits & Systems Group (LiNCS)
Description The internet of things paradigm poses a whole set of new challenges: among others how supply power to a network of wireless sensors and actuators. Batteries are not always a feasible solution because of dimension constrains and/or remote and difficult to access positioning.
Energy harvesting describes a set of technical solutions to realize devices capable of self-powering, by collecting power from the surrounding environment in the form of parasitic mechanical/sound vibrations, thermal power or dispersed electromagnetic energy. Mechanical vibrations are particularly attractive, because of their almost ubiquitous presence and their relatively high energy density.
Mechanical energy can be converted into electric power exploiting different physical principles, e.g. piezoelectricity, electromagnetic induction or capacitance variations. With advances in micro–electro–mechanical (MEMS) technology, it is possible to implement a self powered system with the MEMS device acting as an electromechanical transducer that exploits piezoelectric material vibrating beams, micro inductors or variable capacitor. The common feature of MEMS transducers is the presence of an oscillator as transducer, that has to be tuned on a resonant frequency.
The candidate will learn foundation of noise and random fluctuations in electronic systems, together with technology of energy harvesting and MEMS. He will learn and apply state of the art techniques for modelling, analysis and design of energy harvesting systems.
The candidate will be involved in the study of an innovative energy harvesting architecture, currently under development by LiNCS (Linear and Nonlinear Circuits & Systems) group at Politecnico di Torino, in collaboration with the DISAT department and MemComputing Inc., San Diego, CA, USA.
The candidate is expected to contribute actively to the development of a circuit simulation software for dynamics modelling and energy efficiency estimation.
Required skills Good background in electronics, circuit theory and programming skills (MATLAB) are required. Candidates with good knowledges in physics and stochastic process are encouraged. Part of the work configures as research activity. Working enthusiasm, creativity and attitude to problem solving are welcome.
Notes This thesis is in collaboration with the start up MemComputing Inc., San Diego, CA, USA. Contact person Fabio Lorenzo Traversa, phD.
Deadline 30/08/2024
PROPONI LA TUA CANDIDATURA