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List:       kde-panel-devel
Subject:    Re: battery plasmoid and remaining time..
From:       Andrew Coles <andrew_coles () yahoo ! co ! uk>
Date:       2009-05-19 11:44:22
Message-ID: 449681.17681.qm () web25905 ! mail ! ukl ! yahoo ! com
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> 1) what methods of time estimation can we think of? (eg. the current one-point 

> method, averaging over X amount of time...)

Without being able to add sensors into the battery itself, what we are left with is a \
machine learning problem: predict, on the basis of what can be measured, the \
remaining battery life.  The two biggest influences on this are the remaining \
capacity, obviously, and the power draw - if we draw exactly double the current, the \
battery won't last exactly half as long.  Temperature is another influence, but I'll \
leave that for now.  With these measurements, we then need some sort of model on \
which to base our predictions.  This is where the learning comes in: battery models \
depend on what battery it is, how old it is, how it's been used etc. etc. We cannot \
possibly hope to guess what a reasonable battery model is, but we can approximate one \
over time.

One way to do this is to record an average figure of how long each % of battery life \
lasts, normalising for power draw.  We'd have a figure d for how long the % from 96 \
to 95 lasts, obtained over n discharge cycles, and every time we get a new figure c \
for this (on the current discharge cycle):

d' = (n*d + c) / n + 1

Then, to find remaining time - given the current power draw - sum these figures from \
the current charge to 0%, and adjust for power usage.

(Wrapped up in that is the assumption that we can 'normalise for power draw'.  That \
necessitates a separate model, using similar techniques: learn the relationship \
between the load and the discharge rate.)

So, doing this 'right' is non-trivial, which is probably part of the reason why it \
hasn't been done before.  It comes back to what Aaron was saying: there's so much \
going on, it's hard to be precise.  We could do a bit better than the current \
situation, providing estimated time remaining for current conditions, so at least \
reported time left adjusts for a USB toaster being plugged in.  We could also report \
how much time is left if the user cuts back on power usage.

It's still an open area of research, if you want to do a literature survey - without \
being able to put sensors into the battery, we're basically left with software \
models.  It's not something I have time to do myself, but I can put my Dr Coles hat \
on to field questions on the learning/prediction/AI side of things if someone else \
wants to work on this topic.

Andrew



      
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