IEEE Circuits and Systems Magazine - Q3 2018 - 28

I. Introduction
he increasing need for passive self-powered sensors demands advanced technology to scavenge
energy from the surrounding environment [1]-[4].
Energy harvesting is a promising technology that can be
adopted to power Wireless Sensor Nodes (WSNs), implantable bio-devices, or mobile applications. This technology can be employed to improve the battery lifetime of
the target system, or ultimately to implement battery-free
and low-maintenance electronic devices.
The research on novel harvesting methodologies
elicits valuable standalone monitoring systems. Hence,
the demand for energy harvesting solutions thrives on
many sectors, as shown in Fig. 1 [5].
Burgeoning energy harvesting applications, shown in
Fig. 2, exploit thermal, kinetic, solar and Radio Frequency
(RF) waves as power sources. Considering the aforementioned energy harvesting strategies, photovoltaic cells
yield the highest power density (. 10 mW/cm2 in outdoor
condition) [7]. The exploitation of solar power inherently
imposes constraints on the possible target application
since light is not always accessible, e.g. in implantable energy harvesters. Furthermore, light sources could be inconsistent throughout the day since they are strongly dependent on environmental conditions. Thermal gradients
and temperature variations enable harvesting strategies
exploiting the thermoelectric and pyroelectric effects.
Thermal transducers retain a high power density (up to
10 mW/cm2 for industrial application) [8]. Thermal energy
hinders the same limitation of solar energy, since a sufficient temperature gradient or variation is not ubiquitously
present in nature. Conversely, RF waves are continuously
accessible in both rural and urban areas, indoor and outdoor. Albeit RF waves substantiate a reliable harvesting
source, the attainable power is strongly dependent on the
distance from the transmitters.
It is possible to scavenge energy from the environment by exploiting ambient mechanical stimulations. Vibration of piezoelectric transducers is the most adopted
method of scavenging mechanical energy for two main
reasons: piezoelectric materials are easy to integrate on
chip, and they are able to generate a high power density,
up to 375 nW/ cm 3 [9].

Different types of mechanical structures have been successfully employed to scavenge vibrational energy [10].
The most common topologies are based on a cantilever
beam configuration [11]-[17], or on a plate configuration
[18]-[23]. Other alternative mechanical structures exploit
piezoelectric windmill transducers [24], [25], piezoelectric
"cymbal" transducers [21], [26], or long piezoelectric polymers [27], [28] to harvest energy from the environment.
Most of the vibrational energy available, utilizing
piezoelectric transducers, is concentrated on one frequency tone that varies over time due primarily to a
variation in the mechanical excitation [29]. To efficiently
extract most of the mechanical source energy, many electronic and mechanical techniques have been proposed
to increase the frequency band of the electromechanical system. It is possible to expand the frequency bandwidth by exploiting two properties of vibrational energy
harvesting systems: the equivalence between vibrational
and resonant frequency (the techniques exploiting this
property are summarized in [30]) or the equality of electrical and mechanical damping [31]-[35].

Wearable
2%
Health
Monitoring
Phones
1%
7%

Industrial
10%

Laptops
6%

WSN
14%
Energy Harvesting
Market Share in
2017
US$1.5 bn

Consumer
Electronics
45%

Military
and
Aerospace
15%

Figure 1. energy harvesting market share in 2017.

Francesco Dell' Anna is with Chongqing Key Lab of Micro-Nanosystems Technology and Smart Transducing, Chongqing Technology and Business University CTBU, Chongqing, China, No.19, Xuefu Ave, Nanan District, Chongqing, P.R.China 400067 and Faculty of Engineering, Science and Maritime
Studies Department of Microsystems, campus Vestfold, Høgskolen i Sørøst-Norge Postboks 235 3603 Kongsberg. Tao Dong (Corresponding author)
Faculty of Engineering, Science and Maritime Studies Department of Microsystems, campus Vestfold, Høgskolen i Sørøst-Norge Postboks 235 3603
Kongsberg (e-mail: Tao.Dong@usn.no) Ping Li and Wen Yumei are with the Department of Instrumentation, School of Electronic Information and Electric Engineering, Shanghai Jiao Tong University, 200240, Shanghai, P.R.China. Zhaochu Yang is with the Institute of Applied Micro-Nano Science and
Technology, Chongqing Technology and Business University Chongqing, No.19, Xuefu Ave, Nanan District, Chongqing, P.R.China 400067. Mario R. Casu
is with the Department of Electronics and Telecommunications (DET), Politecnico di Torino, Corso Duca degli Abruzzi, 24-10129 Torino. Mehdi Azadmehr and Yngvar Berg are with the Faculty of Engineering, Science and Maritime Studies Department of Microsystems, campus Vestfold, Høgskolen i
Sørøst-Norge Postboks 235 3603 Kongsberg.

Ieee cIRcuITs anD sysTems magazIne

THIRD quaRTeR 2018

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