The flourishing of the Internet of Things (IoT) paradigm has posed impressive new challenges concerning the problem of powering small, wearable or remote electronic devices.
In this field, batteries represent the current dominant technology, but their limited power density, their short life, the difficulties and costs required for their replacement, and their significant environmental footprint call for the development of new solutions. An alternative to batteries is represented by energy harvesting, which consists of the collection of energy from the surrounding environment: such energy, which would be otherwise lost, can be successfully employed to power autonomous electronic devices.
Within this framework, the purpose of the ENEHRVIT project is twofold: on the one hand, new innovative configurations are introduced and their effectiveness is evaluated, and, on the other hand, issues concerning state-of-the-art technologies are addressed by developing new techniques to determine their impact and, hence, to outline the most efficient operations of such devices.
The final outcome is a set of software tools that can be used to test and optimize both conventional and new harvester configurations, prior to their practical implementation. An additional value is provided by the different methodologies that have been employed in the analysis, which include linear models, nonlinear dynamics techniques and stochastic analysis methods.
To draw the conclusions, not only does the value of the ENEHRVIT project lie in the developed software tools, but also in the comprehensive methodology that has been followed, which combines a deterministic and a stochastic approach, allowing to study and optimize energy harvesters under different and complementary perspectives.
PRINCIPAL ACADEMIC TUTOR
Michele Bonnin, DET, Politecnico di Torino
OTHERS ACADEMIC TUTORS
Fabrizio Bonani, DET, Politecnico di Torino
Carlo Ricciardi , DISAT, Politecnico di Torino
Stefano Stassi, DISAT, Politecnico di Torino
Federico Bizzarri , DEIB, Politecnico di Milano
Angelo Brambilla, DEIB,Politecnico di Milano
MemComputing Inc., San Diego, CA, USA
Fabio Traversa, MemComputing Inc.
Alessandro Giammarini, Mathematical Engineering Politecnico di Torino
Federico Parolin, Energy Engineering Politecnico di Milano
Lorenzo Rosso, Physics of Complex Systems Politecnico di Torino
Davide Zurovac, Aeronautical Engineering Politecnico di Milano
Alessandro Diano, Electrical Engineering Politecnico di Milano
Claudio Del Sole, Mathematical Engineering Politecnico di Torino
Jacopo Baglioni, Nuclear Engineering Politecnico di Milano