How to Debug Your Battery

> If you collect 3 different data points changing each thing one at a time (original design, some number higher, some number lower) whilst keeping everything else constant (usually a good scientific approach) that's 320 possible combinations of changes!

There is an entire field of statistics (Design of Experiments) where one of the first lessons you learn on day one is how one-factor-at-a-time testing is one of the most inefficient ways you can test something. It’s usually only done out of ignorance to better methods by those with little to no formal statistical training.

An experiment designed by someone who is well versed in modern experimental design methods would not take billions of runs to optimize—a sequential design that first screens out factors to those that matter (basic Pareto principle) followed by a response surface design or a GP model surrogate to optimize the response would likely be on the order of hundreds (possibly thousands) of runs. This is basic industrial experimentation—see “Design and Analysis of Experiments” by Douglas C. Montgomery for a nice introductory textbook.

I’ve been on a journey to learn a bit about battery tech by building my own “solar generator”. Terrible name, but something like a jackery or blue yeti.

I acquired 4 lithium iron phosphate cells along with a bms, solar charge controller and various doodads.

I had to learn about balancing the cells, wiring, etc. it’s been a bit of a rabbit hole for sure.

I ended up building 1.2kwh battery for powering my fridge and lights while camping. For less than half the price of an equivalent off the shelf unit. Of course it has taken an enormous amount of learning, but that’s free.

One the more interesting revelations to me, is how much I under appreciated industrial design before. On the first glance a device like a battery pack is a square box with a couple of outlets but I’ve certainly had a difficult time making it look nice. Internal component wiring is also an interesting challenge.

For those interested in energy profiling tools that have applications for developing battery powered hardware products I can highly recommend Nordic Semiconductor’s PPK II. For a reasonable price you get a hardware tool and software kit that can profile your actual energy usage quite well. It has punched well above its weight on providing power profiles against tools an order of magnitude higher in price. If you are designing a hardware product that runs on battery a tool like this is a necessity.

I know above sounds like an advertisement but it isn’t. I’m not affiliated with NS at all. It’s just a great tool and I’m happy to recommend it as there are very few cost effective options in this space.

Thanks for posting this. PyBAMM is really slick. I first learned about it from a webinar on the competing Julia package.

I have to ask though, how many organizations are really designing their own cells for new products? And how much validation have these packages had? I know it's expensive and time-consuming to get a lot of battery discharge data. My experience may be overly coloring my thinking here - my idea of battery modeling involves a circuit simulator and only those effects that are not going to be drowned by the large tolerances in common batteries.

The one area where more detailed physical modeling would be interesting would be in long-term degradation and wear modeling for secondary cells. Is there a tutorial or example along those lines?

It would be interesting to see a blogpost on parameterizing a model in PyBaMM given a commercial cell. I imagine many battery engineers using simulation-based design tread over the same ground for determining parameters from literature, X-rays, etc.

Everyone is always reinventing blogging platforms and personal blog sites when GitHub was the perfect solution all along.

Extremely terse. Not much about Debugging my battery, or my specific battery in particular, but batteries in general, and profiling them in a few stochastic qualitative measurements.

I.e. Requirements: "pybamm=24.1"

https://github.com/pybamm-team/PyBaMM

I found the article interesting but I don't think "debug" is the right word here. I was thinking the article would be about debugging a software or electronics bug that causes my laptop or car battery to drain too fast.

Maybe it should have been titled, "How to model the right battery choice for your application" or "Understanding trade-offs in battery design".

Is the library parametric such that it works for other electrolyte systems like sodium batteries? How about flow batteries? I would think cracking isn't such an issue for 2 fluids across a membrane.

Or even just lead-acid?

ie is this 'debug lithium'

For anyone interested in the performance requirements for electric flight, alluded to but not explored in the article. This is a great open-access paper about it https://pubs.acs.org/doi/full/10.1021/acsenergylett.8b02195

Very cool!

At Gouach (https://get.gouach.com) we're building a battery framework which requires no welding, nor glue, which makes it easy to repair, refill, and tweak batteries safely!

We develop our own BMS that we made to be really powerful and extensible (focusing mainly on light electric vehicles, e-bikes, e-scooters, e-mopeds etc)

We'd love to see how your platform (or PyBaMM) could help us improve our SoC / SoH estimations, and remaining capacity estimation. Would you have any pointers / tutorials on this?

Can you use energy batteries to recharge power batteries which handle transients, or install them in parallel?

> This is known as the curse of dimensionality (the more things you have to vary, the exponentially more combinations you have to test)

Is this really a valid usage of this term? The only definition I am personally familiar with is from machine learning, and it is something totally different.

thanks for sharing...

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