The new chips, such as Analog Devices ADP5090 power
boost regulator (Figure 3) maximize the efficiency of energy
harvesting capabilities by using specialized techniques
such as maximum power point tracking (MPPT), and thus
guarantees the maximum power extracted from the energy-harvesting source.
There have been improvements in the energy storage
front as well. Take the case of supercapacitors used to
buffer and store power in energy-harvesting applications.
The battery-backup devices, like supercapacitors, also
provide charge to energy-harvesting systems when the
battery is exhausted and there is no power supply available.
Leakage current is a critical issue in supercapacitors.
When supercapacitors are applied to energy-harvesting
applications to maximize power consolidation, energy
wastage due to current leakage and power dissipation is
not acceptable for designers.
Chipmakers like ALD are now offering power MOSFETs
that compensate leakage current by lowering the operating
voltage of the leakier supercapacitor. That way, MOSFETs
automatically balance voltage in each cell and help facilitate
ultra-low-power operation in energy-harvesting systems that
otherwise take days to charge the required levels of current.
The above example of auto-balancing shows how low-power circuits are quickly improving. Add that to the
advances in energy transducers and sensors, and what
you see is energy harvesting quickly becoming feasible in
places unimaginable just a few years ago. One such case is
energy harvesting via a wireless sensor network.
Wireless Sensor Nets
Wireless sensor networks used for smart lighting, home and
building automation, remote asset monitoring and presence
detection are classic examples of an energy harvesting
application (Figure 4). A wireless sensor node can employ
vehicle vibrations to power sensors on a bridge or use
solar-powered sensors for wireless monitoring of a farm,
A wireless sensor node—comprising a
sensor, a microcontroller or microprocessor
and an RF module—works in tandem with an
energy harvesting system to create a complete
monitoring application. The Japanese firm
Murata claims that its wireless sensor node
requires as little as 100 μ W of energy to be
However, while engineers at Murata are
confident that they are past the challenge of
matching an energy harvesting device with a
sensor node, they acknowledge that there are
still hurdles to overcome.
Again, one of the key obstacles in the
widespread use of wireless sensor nets has
been the change of batteries. The development
of chips consuming very little power, and the availability
of battery-backup devices like supercapacitors, will allow
energy harvesting systems in wireless sensor networks to
operate for longer periods of time without battery changes.
Moreover, new power management ICs could help
create batteries that can last 10 years or longer. Another
critical factor benefitting energy harvesting applications,
such as wireless sensor nets, is the advent of low-cost IoT
gateways. These gateway devices maximize the efficiency of
energy harvesting capabilities by offering more processing
power at the network edge.
It’s apparent that Io T is providing the basic impetus for the
energy-harvesting industry to turn the corner. Another way
to see this intertwined technology relationship is that energy
harvesting is rapidly evolving to meet the requirements
for low power consumption in Io T systems. Continued
improvements in power management ICs, battery charging
components, microcontrollers, and other devices will give
designers more options for building energy-efficient sensor
networks. And that makes energy harvesting one of the key
tenets of the Io T revolution.
Figure 3: Analog Devices’ ADP50590 power boost regulator converts DC power from
photovoltaic (PV) cells or thermoelectric generators (TEGs), to charge storage elements like
rechargeable Li-ion batteries, thin-film batteries, supercapacitors, etc. (Source: Analog Devices)
Figure 4: Wireless sensor networks used for smart lighting, home and building
automation, remote asset monitoring and presence detection exemplify energy