tomtranter

Agents don’t need sound effects. But I do.

I made a tiny Python “music alert” for when my agents finish running: original dual-track chiptune jingles with a properly raunchy bass line.

success → end-game credits vibe failure → nervous twitchy riff quick tasks → microwave ping

It’s opt-in (env var gated), so CI stays quiet.

Completely unnecessary. Weirdly addictive. And a great way to make “done” impossible to miss.

What’s your best unnecessary-but-useful dev hack?

My biggest frustration as an academic was reproducibility of papers I was reading. The pdf is such a useless medium for information transfer and the academic publishing industry is a complete racket where all the value is generated by the authors and reviewers who work for free and have to pay (in most cases) to have their work accessible freely to the public. I would love to see this turn into a default way to publish papers

Also good point on degradation. Physics based modelling is invaluable for debugging this. PyBaMM does have quite a bit on degradation yes. Here's a good notebook to start with https://docs.pybamm.org/en/stable/source/examples/notebooks/...

Good question. I would say anyone developing new materials in a lab would benefit from the kind of physics-based models we have in PyBaMM. Organizations is a pretty broad term but I assume you mean companies in which case probably the number as a fraction of all companies dealing with batteries in some way is quite small, but the value of those companies is disproportionately large - think big car manufacturers and also companies dealing in more extreme environments like aerospace and also for heavy vehicles e.g. Fortescue who are electrifying their mining trucks. All the companies building cells and materials for cells doing cell design will certainly benefit from physical modelling. Validation of the packages is strong - PyBaMM has many peer reviewed citations. Validation of the numbers in the simulations for specific cells is probably weak and that's a real pain point in the industry that ionworks is working to address

Yeah I thought so but like most legends contains a kernel of truth and is certainly worth remembering for the lesson. Reminds me of the midwit meme https://www.ycombinator.com/library/IW-dalton-michael-elon-m...

PyBaMM predates ChatGPT. But we're emulating cyclers which are fairly basic tbh. I'm exploring ways of using LLMs to improve the experience. ie Cycle my NMC-Gr 18650 with a CCCV at 1C with an RPT cycle of CCCV and GITT at C/10 every 10 cycles until 80% capacity using model options x,y,z

Thankyou

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

Hahaha. No marshmallow instructions for us yet but some people are using PyBaMM to model thermal runaway. We don't use an LLM but I guess could in order to catch more edge cases. There is an experiment class and a step class. Each step can be called with arguments or passed a string that equates to the same thing but you will get errors if you mistype or leave something out. https://docs.pybamm.org/en/v23.5_a/source/api/experiment/exp...

Related topic there is this example combining PyBaMM and pints for sensitivity analysis. Which should definitely be done first before delving straight into a DOE https://github.com/pints-team/electrochem_pde_model

I used Hall effect sensors for a project and found they needed a fair bit of calibration. Shunt resistors also did the job with fewer problems but this was a 16p2s module.

Hopefully. The thing that makes most sense is two-way charge points but for whatever reason these aren't that common

Nice! I love the simple approach like the story which I'm not sure if it's true or not that NASA spent $$$ developing an ink pen that would work in zero-g and the Russians used a pencil.

Yes completely agree. This is one of the things that PyBaMM doesn't do for you out of the box. I could have extended the article in many ways to cover all the optimizations you could do both with the physical battery or the model. Thanks for sharing the text book. I think my point which I should have stated more clearly was that maybe for smaller design spaces this might not be a bad approach but with batteries the space is huge. I co-authored a paper on optimally reaching the Pareto front using the and problem as an example actually. may be interesting reading for anyone else coming to this area. https://www.sciencedirect.com/science/article/abs/pii/S03062... Happy to share the pdf with anyone who wants to read the whole thing

Fantastic! I will now enter the rabbit hole

*NO LARGE LANGUAGE MODELS WERE HARMED IN THE CREATION OF THIS CONTENT*

Every blog should be able to have pull requests eh

Amazing thanks, my vscode spell checker missed that because of the *Ba*

Yeah thanks for the extra insight. On the modular modelling system bit, this is something we're not particularly good at telling people or highlighting. You can solve any PDE you want with PyBaMM but a lot of the high level battery models have been built upon several classes of lower level models that make battery specific assumptions. The Oxford University software research group headed by our good friend Martin gave a really nice intro course this year which helps you build a model from scratch which I find always helps with understanding https://train.rse.ox.ac.uk/material/HPCu/libraries. We should do more non-battery examples too, there is this one solving transient heat conduction in a rod https://docs.pybamm.org/en/latest/source/examples/notebooks/...

Great concept. Now I want an e-bike even more. Yeah I'd be happy to chat. My contact details are in the readme.

Yes this should be possible. I think the main constraint would be keeping the cell chemistry the same so that OCP is similar. I've been playing with a pack model of cells with mixed capacity using another open-source tool in our pybamm-team collection https://github.com/pybamm-team/liionpack

haha - indeed

Thanks for the advice, I have followed it

Haha - yes. all you need is a readme and a python package that can generate gifs. We put this in PyBaMM for our BattBot project https://github.com/pybamm-team/BattBot which was done by this awesome GSOC student who now works at CERN!

By the way if I was to edit the title I would put "design" at the end but I can't find how to do this? Not a very regular poster I have to admit

That's a fair point. I guess I used it a bit too freely but I have the habit of introducing programming terms into everyday life. It's trying to understand why something is suboptimal

Good to know, do you develop battery powered hardware?

That's cool. I'd love to be able to do that but my hacking skills are somewhat confined to the digital domain. What's going to be really interesting in the next few years is the number of batteries coming out of cars which could be re-purposed for grid storage or back-up domestic power like your set-up here. Typically an ev battery is determined to be at end-of-life when it's reached 80% of original capacity. However, the capacity is also dependent on how fast you try to cycle it and over what range of SoC. The bigger the SoC window and the faster the cycling the more stress put on the battery and the larger the losses. Taking batteries out of cars and putting them in boxes, cycling them slowly and within a smaller SoC window means you can get a lot more life out of them.

Yes, parameterisation is incredibly important. The classic recent example from academia that heavily features in PyBaMM is Chen2020 which is a very thorough case study of collecting data. https://iopscience.iop.org/article/10.1149/1945-7111/ab9050 There has also been a subsequent review article on the subject https://iopscience.iop.org/article/10.1088/2516-1083/ac692c/.... If you are looking for a more hands on guide then there are also open-source tools for parameterizing models https://github.com/pybop-team/PyBOP and https://github.com/paramm-team/pybamm-param

I'm sorry that you found it terse. I intended this as a brief intro and would encourage people who found it a little bit interesting or relevant to their problems to either read the more extensive examples on PyBaMM. If of interest, Silicon anodes are only one type of material being extensively researched in order to improve batteries. The holy grail is Lithium metal where there is no host material on the anode side at all. This would give the ultimate energy density but has so far largely eluded commercialization.