Tech Briefs Magazine - February 2022 - 36

Power & Energy
Artificial Intelligence Improves Battery Health and Safety
A machine learning method promises to predict battery health with 10 times higher accuracy
than the current industry standard.
University of Cambridge, United Kingdom
esearchers have designed a new way
to monitor batteries by sending electrical
pulses into them and measuring
the response. The measurements are
then processed by a machine learning
algorithm to predict the battery's health
and useful lifespan. The method is noninvasive
and is a simple add-on to any
existing battery system.
R
Predicting the state of health and the
remaining useful lifespan of lithium-ion
batteries is one of the big problems limiting
widespread adoption of electric
vehicles and also affects the safety of
mobile phones. Over time, battery performance
degrades via a complex network
of subtle chemical processes.
Individually, each of these processes
doesn't have much of an effect on battery
performance but collectively, they
can severely shorten a battery's performance
and lifespan.
Current methods for predicting battery
health are based on tracking the
current and voltage during battery
charging and discharging. This misses
important features that indicate battery
health. Tracking the many processes that
are happening within the battery re -
quires new ways of probing batteries in
action as well as new algorithms that can
detect subtle signals as they are charged
and discharged.
The researchers designed a way to mon -
itor a battery by sending electrical pulses
into it and measuring its response. A
machine learning model is then used to
discover specific features in the electrical
response that are the telltale sign of
battery aging. The researchers performed
more than 20,000 experimental
measurements to train the model. Im -
portantly, the model learns how to distinguish
important signals from irrelevant
noise. The method is noninvasive
and is a simple add-on to any existing
battery systems.
The researchers also showed that the
machine learning model can be interpreted
to give hints about the physical
mechanism of degradation. The model
can inform which electrical signals are
most correlated with aging, which in
turn allows them to design specific
experiments to probe why and how batteries
degrade.
The machine learning platform is
being used to understand degradation
in different battery chemistries. Optimal
battery charging protocols are being
developed, powered by machine learning,
to enable fast charging and minimize
degradation.
For more information, contact Sarah
Collins at sarah.collins@admin.cam.ac.uk;
+44 (0)1223 765542.
Wearable Biofuel Cells Produce Electricity from Lactate
The biofuel cells can power wearable electronics purely by using human sweat.
Tokyo University of Science, Japan
earable electronic devices and
biosensors are used for health
monitoring but it has been difficult to
find convenient power sources for them.
Scientists have now developed and tested
a wearable biofuel cell array that generates
electric power from the lactate in
the wearer's sweat, opening doors to
electronic health monitoring powered
by nothing but bodily fluids.
Wearable biosensors are generally
meant to be worn directly on the skin in
order to measure specific biosignals and
by sending measurements wirelessly to
smartphones or computers, keep track of
the user's health. Although materials scientists
have developed many types of flexible
circuits and electrodes for wearable
devices, it has been challenging to find an
appropriate power source for wearable
biosensors. Traditional button batteries,
W
36
Cov
like those used in wristwatches, are too
thick and bulky, whereas thinner batteries
would pose capacity and safety issues.
The scientists are exploring efficient
ways of using sweat as the sole source of
power for wearable electronics. A biofuel
cell array uses a chemical in sweat -
lactate - to generate enough power to
drive a biosensor and wireless communications
devices for a short time.
The cell array looks like a paper bandage
that can be worn, for example, on
the arm or forearm. It essentially consists
of a water-repellent paper substrate
onto which multiple biofuel cells are
laid out in series and in parallel; the
number of cells depends on the output
voltage and power required. In each
cell, electrochemical reactions between
lactate and an enzyme present in the
electrodes produce an electric current
www.techbriefs.com
ToC
that flows to a general current collector
made from a conducting carbon paste.
The entire device can be fabricated
via screenprinting, a technique generally
suitable for cost-effective mass production.
This was possible via the careful
selection of materials and a novel layout.
Whereas similar previous cells used silver
wires as conducting paths, the present
biofuel cells employ porous carbon
ink. Another advantage is the way in
which lactate is delivered to the cells.
Paper layers are used to collect sweat
and transport it to all cells simultaneously
through the capillary effect - the
same effect by which water quickly travels
through a napkin when it comes into
contact with a water puddle.
In tests, the paper-based biofuel cells
generated 3.66 V and an output power
of 4.3 mW. To demonstrate their appliTech
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