
Microsoft, Tesla say software-defined batteries could redirect power on the fly - breck
http://www.pcworld.com/article/2988945/mobile/microsoft-tesla-say-software-defined-batteries-could-mix-and-match-power-on-the-fly.html
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csirac2
This is a useful [white]paper in the sense that it has everything in one
place, but the disgusting overuse of "software-defined" means I had to
overcome a fully pegged internal B.S. meter while trying to read it.

What I mean is: surely a "software-defined" battery would be some kind of
redox/flow battery where you can literally adjust the physical properties of
the battery to suit the current SOC and current/anticipated system demands.

Don't get me wrong, we need more work like this, particularly if Tesla
powerwall home batteries and the like are going to become a thing that we
don't want filling landfills with avoidable charge/discharge cycles.

But wow, SDx. I mean, SDR is obvious; software-defined radios clearly replace
fixed hardware with programmable IFs and tonnes of DSP. Similarly, networks
can be software-defined if they replace discrete stand-alone equipment with
fewer tiers of more capable hardware delineated more by
connectivity/performance than function.

When it comes to this paper though, nothing is being replaced. And again, it's
useful work, particularly in the context of consumer applications (cf.
aerospace which has already had to produce systems that do funky, adaptive,
predictive, cooperative load/charge management across multiple battery
chemistries).

I don't know what I'm saying. It's an interesting paper, but as someone
working on low-power systems and exploring different battery chemistries for
different things, the whole SDx angle somehow cheapens it... but perhaps I'm
just weird.

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ape4
Yes, it is just software _regulated_ or software _controlled_.

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pilom
Why can't all of this just be done in the charge controller? The logic seems
pretty simple. When plugged in, accept all power, charge the high capacity
battery at its highest rate, any extra power available goes to the fast
charging battery. On discharge, discharge the fast charging one first. Unless
there are differences in charging efficiency between the batteries, I don't
see how software with knowledge of my schedule could make things better?

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skywhopper
Agreed. This story didn't provide any examples that made sense to me about why
there would need to be different charging strategies in different situations.
If you have your device plugged in overnight, then it will be fully charged no
matter what strategy you use. If you have it plugged in for only a short time,
you will have wanted it to charge as fast as possible during that time, so the
battery should choose whatever charging pattern maximizes energy storage at
the current charge levels.

I had expected this story to tell me that different battery chemistries react
differently to different drain patterns, ie that low-drain usage might be
better served by battery chemistry X and spiky high-drain usage by battery
chemistry Y, and the OS could switch the power source between the batteries
depending on the predicted near-future discharge pattern, based on what app
was foregrounded or whatever.

But the idea that your battery would benefit by knowing your flight schedule
seems to be reaching pretty far for a justification.

~~~
csirac2
If you can bring yourself to get past the SDx marketing bandwagon, the paper
covers multi-battery and multi-chemistry systems. Laptops aren't the obvious
use-case for this. Given that Tesla is involved, they're thinking more along
the lines of cars and home/office energy storage, where you have a large and
diverse set of batteries to manage, and interesting real-time pressures you
just don't see in a laptop.

BMS in a laptop mostly just has to keep the battery safe and avoid unnecessary
charge/discharge cycles. In a more complex system trying to salvage every
joule of energy and maximize lifespan of each cell, the fact that batteries
are less efficient to charge (or discharge) the closer they are to full (or
empty) might be taken into account when deciding which to charge/discharge
(for example).

A car might dump sudden regenerative braking power into high-C batteries if
the main batteries can't take that charge at a given instant.

Satellites often use exotic batteries able to fully charge and discharge 10
times a day for decades at a time, but these have enormous self-discharge
rates measured in days. Every chemistry has a unique set of compromises. There
is plenty of room for smarter BMS in consumer systems that manage complex
battery storage arrays responding to thermal, aging, cycle count, charge and
load pressures more intelligently.

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Animats
This has been suggested before, with combinations of ultracapacitors and
batteries.[1] When a electric vehicle with regenerative braking brakes hard,
that can produce more power than the battery can accept for charging. Dumping
the energy into ultracapacitors is a good way to store it for a short period.

Laptops? Probably just a gimmick. It won't increase the stored energy.

[1]
[http://www1.eere.energy.gov/vehiclesandfuels/pdfs/merit_revi...](http://www1.eere.energy.gov/vehiclesandfuels/pdfs/merit_review_2009/vehicles_and_systems_simulation/vss_15_bohn.pdf)
[2] [http://www.technologyreview.com/news/417053/a-battery-
ultrac...](http://www.technologyreview.com/news/417053/a-battery-
ultracapacitor-hybrid/)

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userbinator
After seeing the associated considerations of forced obolescence/vendor lock-
in, I'm not so convinced we should have more software in batteries... and
that's not even getting into the basic idea that it's _yet another thing to go
wrong_ , whether security-wise or else.

 _your device would learn how to charge, just as it learns your schedule, your
voice, and other things about you_

...no thanks.

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Too
I would prefer more manual control than trusting some kind of AI calendar
understanding that a scheduled flight will require a charged battery, that
also requires me to actually schedule the flight in said calendar. Case in
point is lenovos charging algorithm, they tried to be smart, probably with
same intentions as Microsoft is here, by only charging the battery to 83% on
normal days because that supposedly reduces the wear of the battery if you
frequently move the laptop. Problem is I was actually on my way to a flight
and there was no override, I had plenty of time but the battery simply
wouldn't go up any more. After the trip I found the option, in some obscure
menu only available after installing a special battery control program, you
choose between battery life and battery performance, guess which one does
what..

With that said I don't think the concept itself is bad, its just that the
execution will inevitably fail except under very regular circumstances such as
carrying your laptop back and forth to the office each day. Volvo trucks has a
similar thing to save fuel for their gearboxes that automatically chooses gear
based on the performance you got the last time you drove that very route.

~~~
csirac2
Statistically though, these approaches can really reduce cycle count - even if
they sometimes get it wrong.

But it's not just anticipating demands by learning past behaviour. There's
also the problem in any multi-battery system (which is what they cover), let
alone with multiple types, optimizing what should take charge or load at a
given time. Most people don't realize that many battery chemistries actually
don't have a flat efficiency rating with charge: often, the closer to 100%
charged you get, the less efficient (more loss) you have compared to what
you'll be able to extract later.

For example, charging from 0 to 100% might be 85% efficient for a given
battery type. But charging it from 80% to 100% full might only be 40%
efficient.

And this variable efficiency also applies to discharge as well. And the
variables all change with what recent battery demands have been, let alone the
current loads - but also cell voltages, temperature, age and cycle count.

Even planning to cope with self-discharge over days, weeks or months might
benefit from smarter BMS. Some battery management systems even take into
consideration thermal management (taking into account the cost of ramping up
active cooling or throttling charge rates to keep batteries at a temperature
efficient for taking charge).

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dbyte
Wow, I was looking forward to see what other acronym people can think of in
the Software-Defined-Something family (SDx).

I'm wondering if other BMS (Battery Management Systems) used in other domains
are not already doing what they propose in the paper.

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mkonecny
All this "smart" learning software feels really gimmicky to me. Anyone
remember Windows Vista had this heavily marketed feature that would "learn"
how you use your apps at certain time of the day, and therefore allow you to
launch them faster by pre-caching a few minutes before your expected launch.
This feels similar.

The Nest thermostat I have at home promised to save me energy by learning my
schedule, and heating the house only when needed - I had to turn this off
because it never really worked. People do not inherently have a predictable
schedule anyway.

The leaving for the airport in 15 minutes example in this article is similarly
contrived.

Perhaps using multiple types of batteries will be useful in the future, but
I'm not sold on the software learning part ATM.

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iamleppert
tl dr; Low on substance and high on hype.

